NLP in Healthcare and Life Sciences Market by Component (Solutions and Services), NLP Type (Statistical, Hybrid), NLP Technique (IVR, OCR), Application (Clinical Trail Matching, Drug Discovery), End Users and Region - Global Forecast to 2027
Updated on : April 6, 2023
NLP in Healthcare & Life Sciences Market Analysis
The global NLP in healthcare and life sciences market in terms of revenue was estimated to be worth USD 2.2 billion in 2022 and is poised to reach USD 7.2 billion by 2027, at a CAGR of 27.1% from 2022 to 2027. An analysis of market trends is part of the new research report. The latest research study includes conference and webinar materials, patent analysis, important stakeholder information, and pricing analysis. Various factors such as rising demand for NLP systems programmed to understand the context of medical records, and the evolution of cognitive computing to fuel the demand for NLP solutions for precision medicine applications are expected to drive the adoption of NLP solutions in healthcare and life sciences market.
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NLP in Healthcare & Life Sciences Market Dynamics
Driver: Growing need to analyze and extract insights from narrative text and huge amount of clinical data
The need for better use of unstructured data is being driven by changes in business models and outcome expectations. 20% of the healthcare data that is received in structured format through clinical channels has been the main focus of traditional health information systems. In order to improve patient care and streamline workflow, NLP can automatically extract patient information from free-form, unstructured language. This actionable data is then produced. The most important clinical data items, such as issues, social history, prescriptions, allergies, and procedures, can be tagged by well-designed NLP systems, which can also assess text-free dictation and comprehend situations. The preferred working environment of doctors can incorporate NLP, allowing both real-time and background dictation procedures. Before committing information to EHRs, physicians can interactively self-edit texts and clinical facts as they appear on the EHR screen thanks to NLP's ability to cooperate with speech recognition technologies for the real-time workflow. NLP can be included into a background dictation/transcription workflow to process narrative and produce rich clinical papers that include edited texts and extracted clinical information for doctors' ultimate review and approval. The EHRs process these completed paperwork.
Restraint: Inadequacy in the advancements of NLP technology using neural networks restricting its usage for cloud-based services
NLP is a field of technology that processes sequential data such as text, time series, financial data, speech, audio, and video using neural networks and deep learning algorithms. The most cutting-edge technologies that are enabling NLP to take off in the industry are neural networks and deep learning. However, the creation of these technologies is quite expensive and necessitates a significant investment in both time and R&D funds, which is difficult for small or startup businesses who are trying to establish themselves in the NLP in healthcare and life sciences sector.
For more capacity, a neural network facilitates the precise speech and voice recognition skills in NLP. To comprehend the context, it also computes the enormous volume of user-generated voice data. However, the management of neural network algorithms can only be done by major companies like Apple (US), Microsoft (US), and Google (US). These large corporations use NLP technology to promote their goods and use cloud services offered by neural network-based speech and voice recognition networks. Due to the high infrastructure costs, small businesses in the NLP industry for healthcare and life sciences may not be able to invest significantly in the creation of neural networks. Hence, it restricts the market growth as small players are unable to contribute sufficiently.
Opportunity: The emergence of cognitive computing to boost the demand for NLP solutions for precision medicine applications
Some well-known market firms have made large investments in semantic big data analytics and cognitive computing technologies in the healthcare and life sciences sector. NLP has found uses in the healthcare industry, from the most innovative approaches in precision medical applications to the straightforward procedure of coding a claim for reimbursement or billing. However, creating algorithms that are clever, accurate, and tailored to the practical problems faced by the healthcare and life sciences industries will be essential to the success of deploying this technology. In order to provide patients with an accurate record of their health in a language they can comprehend, NLP will need to achieve the dual aims of data abstraction and data presentation. This improved approach would improve operational efficiency and lower costs in the healthcare sector. When a patient asks a specific question, the cognitive computing system instantaneously evaluates massive volumes of data to provide an immediate answer and generates personalised, intelligent recommendations. In order to determine which treatments are most effective, it is also possible to compare patients with comparable features to cohorts of patients. Cognitive computing also has the ability to bring together various types of data and analyse it contextually. This functionality can assist in resolving a number of IT issues in the healthcare and other industries.
Challenge: Growing regulatory compliance and privacy concerns over data security during COVID-19 slow down the progress of researchers
With the introduction of massive clinical record processing, clinical NLP has a tremendous amount of potential to influence how clinical practices are transformed. However, because of the delayed development mostly brought on by rigorous data access restrictions for researchers, this potential has largely gone unrealized. Data privacy has continued to be a significant barrier to business adoption of AI. AI technologies generate outputs by processing data. Technologies like ML, deep learning, NLP, and emotion recognition draw on the stored data to produce results that can be put to use. To complete activities using smart gadgets or virtual personal assistants like Apple Siri and Amazon Alexa, users must submit a variety of data. The sensitivity of clinical data raises legal and institutional considerations, making it challenging for the NLP community to acquire the pertinent data. For academics who are not affiliated with healthcare organizations, this is particularly true. Clinical notes reveal patient-clinician interactions in which people confide not just their health issues but also their dietary habits and conditions that are stigmatized. In the US, the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, which applies to personal medical data, provides legal protection for this confidential relationship. The General Data Protection Regulation (GDPR) in the European Union (EU) lays out the requirements for the use of health data for scientific purposes (GDPR). The sanitization of sensitive data categories and individuals’ informed consents are at the forefront of these legislative acts and bear immediate consequences for NLP research. Hence, the difficult access to data due to privacy concerns has been an obstacle to progress in the research field.
The solution segment is expected to account for a larger market size during the forecast period
The component segment has been further divided into solutions and services. These solutions can be further bifurcated into clinical variation management, population health management, counter fraud management, and other solutions including risk & compliance management, claim management, and patient care & safety software. The solutions segment is expected to account for a larger market size during the forecast period. These solutions can be used to analyse data gathered from many sources to gain valuable insights and make data-driven decisions about one's health. By turning the free text into standardized data, NLP in the healthcare sector can improve the EHRs' correctness and ensure their completeness. As NLP converts free text into documented data, this could potentially simplify documentation by enabling healthcare personnel to narrate notes.
North America to account for the largest market size during the forecast period
North America is expected to have the largest market share in the NLP in healthcare and life sciences market. Key factors favoring the growth of the NLP in healthcare and life sciences market in North America include the rapid innovation and advancements of AI technologies in the region. The growing number of NLP solutions providers across the region is expected to further drive the market growth in North America.
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NLP in Healthcare & Life Sciences Market - Key Players
The NLP solutions providers have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. The major players in the NLP in healthcare and life sciences market include IBM (US), Microsoft (US), Google (US), AWS (US), IQVIA (US), Oracle (US), Inovalon(US), Dolbey (US), Averbis (Germany), SAS Institute (US), Press Ganey (US), Ellipsis Health (US), Health Fidelity (US), Centene (US), Caption Health (US), Clinithink (US), HPE (US), Oncora Medical (US), Flatiron Health (US), Apixio (US), Forsee Medical (US), Gnani.ai (India), Notable (US), Biofourmis (US), Suki (US), Wave Health Technologies (US), Corti (Denmark), CloudMedx (US), MedlnReal (US), Emtelligent (US).
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Report Metrics |
Details |
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Market value in 2022 |
US $2.2 billion |
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Market value in 2027 |
US $7.2 billion |
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Growth Rate |
27.1% CAGR |
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Largest Market |
North America |
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Forecast units |
USD (Billion) |
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Segments covered |
Component, Organization Size, NLP Type, Application, Deployment Mode, Integrated Technology, End User, and Region |
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NLP in Healthcare & Life Sciences Market Growth Drivers |
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NLP in Healthcare & Life Sciences Market Opportunities |
|
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Geographies covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
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Companies covered |
IBM (US), Microsoft (US), Google (US), AWS (US), IQVIA (US), Oracle (US), Inovalon(US), Dolbey (US), Averbis (Germany), SAS Institute (US) |
This research report categorizes the NLP in healthcare and life sciences market based on component, organization size, NLP type, application, deployment mode, integrated technology, end user, and region.
NLP in Healthcare & Life Sciences Market By Component:
- Solutions
- Services
NLP in Healthcare & Life Sciences Market By NLP Type:
- Rule-based Natural Language Processing
- Statistical Natural Language Processing
- Hybrid Natural Language Processing
By Deployment Mode:
- On-premises
- Cloud
By Organization Size:
- Large Enterprises
- SMEs
By Application:
- Sentiment Analysis
- Drug Discovery
- Clinical Trial Matching
- Risk & Compliance Management
- Dictation & EMR Implications
- Automated Registry Reporting
- AI Chatbots & Virtual Scribe
- Other Applications (Question Answering, Sentiment Analysis, Spelling Correction, and Email Filtration)
By NLP Technique:
- Optical Character Recognition (OCR)
- Interactive Voice Response (IVR)
- Sentiment Analysis
- Text & Speech Analytics
- Image & Pattern Recognition
- Text Summarization & Categorization
- Other NLP Techniques (Predictive Risk Analytics, NER, Auto Coding, Spelling Correction, Email Filtration, Question Answering, and Simulation & Modeling)
By End User:
- Public Health & Government Agencies
- Medical Devices
- Healthcare Insurance
- Pharmaceuticals
- Other End Users (Healthcare research companies, Payers and MedTech)
By Region:
-
North America
- US
- Canada
-
Europe
- UK
- Germany
- France
- Rest of Europe
-
Asia Pacific
- China
- Japan
- India
- Rest of Asia Pacific
-
Middle East and Africa
- Saudi Arabia
- United Arab Emirates
- South Africa
- Rest of Middle East and Africa
-
Latin America
- Brazil
- Mexico
- Rest of Latin America
Recent Developments:
- In July 2022, Google launched a complimentary service called AutoML Entity Extraction for Healthcare, which is a low-code tool for healthcare professionals with minimal coding skills. Moreover, it can be used to create own Healthcare Natural Language models that are customized to derive even more specialized knowledge from medical records – which may be helpful to better recognize more important details in medical records, such as gene mutations and socio-economic factors.
- In May 2022, IQVIA NLP APIs provide instant access to healthcare-tuned NLP, answering crucial questions in healthcare and life sciences at the push of a button, and unlocking a richness to data that can empower decision making. The initial release comprised of a suite of five powerful NLP APIs, designed to answer some of the most common questions in healthcare.
- In March 2022, Microsoft shared a breakthrough solution to simultaneously accelerate unstructured data insights and supercharge interoperability between health organizations: Text Analytics for health structuring to FHIR. This feature of Text Analytics for health enables health organizations to transform unstructured clinical documents into FHIR resource bundles, to deliver better health insights to more people, faster. Text Analytics for health is a generally available natural language processing (NLP) service within Microsoft Azure Cognitive Services that was purpose-built to extract information from biomedical and clinical free text documents.
Frequently Asked Questions (FAQ):
What are NLP solutions?
NLP is the ability of computers to understand the latest human speech terms and text. It is used in current technology to support spam email privacy, personal voice assistants, and language translation applications
Which countries are considered in the European region?
The report includes an analysis of the UK, Germany, and France in the European region.
Which are the key deployment modes adopting NLP solutions?
The key deployment modes adopting NLP solutions are cloud and on-premises.
Which are the key drivers supporting the growth of the NLP in healthcare and life sciences market?
The key drivers supporting the growth of the NLP in healthcare and life sciences market include, the rising urge of predictive analytics technology to reduce risks and improve significant health concerns, growing demand for improving EHR data usability to improve healthcare delivery and outcomes, and the growing need to analyze and extract insights from narrative text and huge amount of clinical data are expected to drive the adoption of NLP solutions.
Who are the key vendors in the NLP in healthcare and life sciences market?
The key players in the NLP in healthcare and life sciences market include IBM (US), Microsoft (US), Google (US), AWS (US), IQVIA (US), Oracle (US), Inovalon(US), Dolbey (US), Averbis (Germany), SAS Institute (US), Press Ganey (US), Ellipsis Health (US), Health Fidelity (US), Centene (US), Caption Health (US), Clinithink (US), HPE (US), Oncora Medical (US), Flatiron Health (US), Apixio (US), Forsee Medical (US), Gnani.ai (India), Notable (US), Biofourmis (US), Suki (US), Wave Health Technologies (US), Corti (Denmark), CloudMedx (US), MedlnReal (US), Emtelligent (US). .
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TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 36)
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.2.1 INCLUSIONS AND EXCLUSIONS
1.3 MARKET SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 2019–2021
1.5 STAKEHOLDERS
1.6 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY (Page No. - 41)
2.1 RESEARCH DATA
FIGURE 1 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: RESEARCH DESIGN
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
TABLE 2 PRIMARY INTERVIEWS
2.1.2.1 Breakup of primary profiles
2.1.2.2 Key industry insights
2.2 MARKET BREAKUP AND DATA TRIANGULATION
FIGURE 2 DATA TRIANGULATION
2.3 MARKET SIZE ESTIMATION
FIGURE 3 MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
2.3.1 TOP-DOWN APPROACH
2.3.2 BOTTOM-UP APPROACH
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): REVENUE FROM SOLUTIONS/SERVICES OF MARKET
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM SOLUTIONS/SERVICES OF MARKET
FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM SOLUTIONS/SERVICES OF NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): COMPONENT LEVEL SHARE THROUGH OVERALL NLP IN HEALTHCARE AND LIFE SCIENCES SPENDING
2.4 MARKET FORECAST
TABLE 3 FACTOR ANALYSIS
2.5 COMPANY EVALUATION MATRIX METHODOLOGY
FIGURE 8 COMPANY EVALUATION MATRIX: CRITERIA WEIGHTAGE
2.6 STARTUP/SME EVALUATION MATRIX METHODOLOGY
FIGURE 9 STARTUP/SME EVALUATION MATRIX: CRITERIA WEIGHTAGE
2.7 ASSUMPTIONS
2.8 LIMITATIONS
3 EXECUTIVE SUMMARY (Page No. - 55)
TABLE 4 GLOBAL NLP IN HEALTHCARE AND LIFE SCIENCES MARKET SIZE AND GROWTH RATE, 2017–2021 (USD MILLION, Y-O-Y %)
TABLE 5 GLOBAL MARKET SIZE AND GROWTH RATE, 2022–2027 (USD MILLION, Y-O-Y %)
FIGURE 10 SOLUTIONS SEGMENT TO DOMINATE MARKET IN 2022
FIGURE 11 PROFESSIONAL SERVICES TO HOLD LARGER MARKET SHARE OF MARKET IN 2022
FIGURE 12 SYSTEM INTEGRATION & IMPLEMENTATION SEGMENT TO LEAD MARKET IN 2022
FIGURE 13 STATISTICAL SEGMENT TO HOLD LARGEST MARKET SHARE IN MARKET IN 2022
FIGURE 14 CLINICAL TRAIL MATCHING SEGMENT TO BE LARGEST APPLICATION SEGMENT IN MARKET IN 2022
FIGURE 15 TEXT CATEGORIZATION & SUMMARIZATION SEGMENT TO BE LARGEST SEGMENT IN MARKET IN 2022
FIGURE 16 CLINICAL VARIATION MANAGEMENT SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2022
FIGURE 17 CLOUD SEGMENT TO HOLD LARGEST MARKET SHARE IN 2022
FIGURE 18 LARGE ENTERPRISES TO DOMINATE MARKET IN 2022
FIGURE 19 PHARMACEUTICALS SEGMENT TO GROW AT HIGHEST CAGR IN 2022
FIGURE 20 NORTH AMERICA TO HOLD LARGEST MARKET SHARE AND ASIA PACIFIC TO GROW AT HIGHEST CAGR
4 PREMIUM INSIGHTS (Page No. - 62)
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 21 GROWING DEMAND TO IMPROVE ELECTRONIC HEALTH DATA USABILITY AND SIGNIFICANT HEALTH CONCERNS
4.2 MARKET: TOP THREE APPLICATIONS
FIGURE 22 AI CHATBOTS & VIRTUAL SCRIBE SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
4.3 NORTH AMERICA: MARKET, BY COMPONENT AND TOP THREE END USERS
FIGURE 23 SOLUTIONS SEGMENT AND PUBLIC HEALTH & GOVERNMENT AGENCIES TO HOLD LARGEST MARKET SHARES IN NORTH AMERICA 2022
4.4 MARKET: BY REGION
FIGURE 24 NORTH AMERICA TO HOLD LARGEST MARKET SHARE IN 2022
5 MARKET OVERVIEW AND INDUSTRY TRENDS (Page No. - 65)
5.1 INTRODUCTION
5.2 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: EVOLUTION
FIGURE 25 EVOLUTION OF THE MARKET
5.3 NLP IN HEALTHCARE AND LIFE SCIENCES: ARCHITECTURE
FIGURE 26 FUNCTIONAL ELEMENTS OF NLP IN HEALTHCARE AND LIFE SCIENCES SOLUTIONS
5.4 MARKET DYNAMICS
FIGURE 27 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: MARKET
5.4.1 DRIVERS
5.4.1.1 Rising urge for predictive analytics to improve significant health concerns
5.4.1.2 Growing demand to improve EHR data usability
5.4.1.3 Growing need to analyze and extract insights from narrative text
5.4.2 RESTRAINTS
5.4.2.1 Specific medical sub-languages and poor input data quality
5.4.2.2 Inadequacy in advancements of NLP technology
5.4.3 OPPORTUNITIES
5.4.3.1 Assembling NLP systems to boost phenotyping capabilities
5.4.3.2 Rising demand for NLP systems to understand context of medical records
5.4.3.3 Emergence of cognitive computing for medicine applications
5.4.4 CHALLENGES
5.4.4.1 Growing regulatory compliance and privacy concerns over data security
5.4.4.2 Interoperability and reliability issues while deploying NLP algorithms
5.4.5 CUMULATIVE GROWTH ANALYSIS
TABLE 6 IMPACT OF MARKET DYNAMICS
5.5 NLP IN HEALTHCARE AND LIFE SCIENCES: ECOSYSTEM
FIGURE 28 ECOSYSTEM OF NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
5.6 CASE STUDY ANALYSIS
5.6.1 CASE STUDY 1: CSL BEHRING USES NLP TO IMPROVE MEDDRA CODING AND ENHANCE QUALITY
5.6.2 CASE STUDY 2: SUPPORTING VALUE-BASED CARE AT ATRIUS HEALTH
5.6.3 CASE STUDY 3: HUMANA REDUCED COSTLY PRE-SERVICE CALLS AND IMPROVED PROVIDER EXPERIENCE WITH WATSON
5.6.4 CASE STUDY 4: BIOPHARMACEUTICAL COMPANY GAINS A COMPREHENSIVE COMPETITIVE ANALYSIS FOR THEIR ONCOLOGY PRODUCTS
5.6.5 CASE STUDY 5: PHILIPS USES AI AND ML TO IMPROVE MEDICAL IMAGING DIAGNOSTICS FOR PHILIPS HEALTHSUITE BUILT ON AWS
5.6.6 CASE STUDY 6: ATHENA BREAST HEALTH NETWORK IMPROVES WOMEN'S HEALTHCARE BY GIVING PATIENTS ACCESS TO THEIR RECORDS
5.6.7 CASE STUDY 7: HEALTHPLIX EMPOWERS DOCTORS IN INDIA WITH AN AI-POWERED ELECTRONIC MEDICAL RECORDS PLATFORM ON AWS
5.6.8 CASE STUDY 8: STRENGTHENING THE FIGHT AGAINST ANTIMICROBIAL RESISTANCE VIA DATA VISUALIZATION
5.6.9 CASE STUDY 9: SECURELY ENABLING AGILE WORLD-CLASS MEDICAL AND PATIENT CARE WHILE BOOSTING SUSTAINABILITY
5.6.10 CASE STUDY 10: SEE-MODE IMPROVES STROKE DETECTION AND PREVENTION WITH ML ON AWS
5.6.11 CASE STUDY 11: CDPHP MODERNIZES INFRASTRUCTURE AND IMPROVES ABILITY TO EXTRACT VALUABLE MEDICAL DATA ON AWS
5.7 SUPPLY CHAIN ANALYSIS
FIGURE 29 SUPPLY CHAIN ANALYSIS
TABLE 7 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: SUPPLY CHAIN
5.8 TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS OF MARKET
FIGURE 30 MARKET: TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS
5.9 TECHNOLOGY ANALYSIS: MARKET
5.9.1 HEALTHCARE TRACKERS, WEARABLES, AND SENSORS
5.9.2 VIRTUAL REALITY
5.9.3 AUGMENTED REALITY
5.9.4 3D PRINTING
5.9.5 ROBOTICS
5.9.6 NANOTECHNOLOGY
5.9.7 BIG DATA
5.9.8 BLOCKCHAIN
5.9.9 IOT
5.10 KEY CONFERENCES & EVENTS IN 2022-2023
TABLE 8 NLP IN HEALTHCARE MARKET: DETAILED LIST OF CONFERENCES & EVENTS
5.11 PATENT ANALYSIS
5.11.1 METHODOLOGY
5.11.2 DOCUMENT TYPE
TABLE 9 PATENTS FILED, 2018–2021
5.11.3 INNOVATION AND PATENT APPLICATIONS
FIGURE 31 NUMBER OF PATENTS GRANTED, 2018–2021
5.11.4 TOP APPLICANTS
FIGURE 32 TOP 10 PATENT APPLICANTS, 2019–2022
5.12 PORTER’S FIVE FORCES ANALYSIS
TABLE 10 IMPACT OF EACH FORCE ON NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 33 PORTER’S FIVE FORCES ANALYSIS
5.12.1 THREAT OF NEW ENTRANTS
5.12.2 THREAT OF SUBSTITUTES
5.12.3 BARGAINING POWER OF SUPPLIERS
5.12.4 BARGAINING POWER OF BUYERS
5.12.5 INTENSITY OF COMPETITIVE RIVALRY
5.13 PRICING ANALYSIS
TABLE 11 AVERAGE SELLING PRICE RANGE OF SUBSCRIPTION-BASED/PAY-AS-YOU-GO NLP IN HEALTHCARE AND LIFE SCIENCES
5.13.1 BUYING CRITERIA
FIGURE 34 KEY BUYING CRITERIA FOR TOP THREE APPLICATION
TABLE 12 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS
5.14 KEY STAKEHOLDERS & BUYING CRITERIA
5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS
FIGURE 35 INFLUENCE OF STAKEHOLDERS IN BUYING PROCESS FOR TOP THREE APPLICATION
TABLE 13 INFLUENCE OF STAKEHOLDERS IN BUYING PROCESS FOR TOP THREE APPLICATIONS (%)
5.15 REGULATORY IMPLICATIONS
5.15.1 GENERAL DATA PROTECTION REGULATION
5.15.2 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT
5.15.3 HEALTH LEVEL SEVEN
5.15.4 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT OF 1996
5.15.5 CEN ISO/IEEE 11073
5.15.6 HIPAA SECURITY RULE
5.15.7 HIPAA PRIVACY RULE
5.16 TARIFF AND REGULATORY LANDSCAPE
5.16.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 14 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 15 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 16 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 17 MIDDLE EAST & AFRICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 18 LATIN AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
6 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT (Page No. - 100)
6.1 INTRODUCTION
6.1.1 COMPONENTS: MARKET DRIVERS
FIGURE 36 SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
TABLE 19 MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 20 MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
6.2 SOLUTIONS
TABLE 21 SOLUTIONS: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 22 SOLUTIONS: MARKET, BY REGION, 2022–2027 (USD MILLION)
FIGURE 37 COUNTER FRAUD MANAGEMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
TABLE 23 NLP IN HEALTHCARE AND LIFE SCIENCES SOLUTIONS MARKET, BY TYPE, 2017–2021 (USD MILLION)
TABLE 24 NLP IN HEALTHCARE AND LIFE SCIENCES SOLUTIONS MARKET, BY TYPE, 2022–2027 (USD MILLION)
6.2.1 CLINICAL VARIATION MANAGEMENT
6.2.1.1 Clinical variation management to boost medical research in coming years
TABLE 25 CLINICAL VARIATION MANAGEMENT: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 26 CLINICAL VARIATION MANAGEMENT: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.2.2 POPULATION HEALTH MANAGEMENT
6.2.2.1 Need to analyze unstructured data to derive insights on non-healthcare factors
TABLE 27 POPULATION HEALTH MANAGEMENT: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 28 POPULATION HEALTH MANAGEMENT: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.2.3 COUNTER FRAUD MANAGEMENT
6.2.3.1 Increasing instances of fraud in healthcare sector due to complex and bureaucratic processes
TABLE 29 COUNTER FRAUD MANAGEMENT: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 30 COUNTER FRAUD MANAGEMENT: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.2.4 OTHER SOLUTIONS
TABLE 31 OTHER SOLUTIONS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 32 OTHER SOLUTIONS: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.3 SERVICES
FIGURE 38 MANAGED SERVICES TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
TABLE 33 SERVICES: MARKET, BY TYPE, 2017–2021 (USD MILLION)
TABLE 34 SERVICES: MARKET, BY TYPE, 2022–2027 (USD MILLION)
TABLE 35 SERVICES: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 36 SERVICES: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.3.1 PROFESSIONAL SERVICES
6.3.1.1 Need to understand unstructured data to enhance enterprise insight discovery and analytics
FIGURE 39 TRAINING & CONSULTING SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
TABLE 37 PROFESSIONAL SERVICES: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY TYPE, 2017–2021 (USD MILLION)
TABLE 38 PROFESSIONAL SERVICES: MARKET, BY TYPE, 2022–2027 (USD MILLION)
TABLE 39 PROFESSIONAL SERVICES: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 40 PROFESSIONAL SERVICES: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.3.1.2 Training & consulting
TABLE 41 TRAINING & CONSULTING: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 42 TRAINING & CONSULTING: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.3.1.3 System integration & implementation
TABLE 43 SYSTEM INTEGRATION & IMPLEMENTATION: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 44 SYSTEM INTEGRATION & IMPLEMENTATION: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.3.1.4 Support & maintenance
TABLE 45 SUPPORT & MAINTENANCE: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 46 SUPPORT & MAINTENANCE: MARKET, BY REGION, 2022–2027 (USD MILLION)
6.3.2 MANAGED SERVICES
6.3.2.1 Customization needs due to ongoing demands and alterations
TABLE 47 MANAGED SERVICES: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 48 MANAGED SERVICES: MARKET, BY REGION, 2022–2027 (USD MILLION)
7 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE (Page No. - 117)
7.1 INTRODUCTION
7.1.1 NLP TYPES: MARKET DRIVERS
FIGURE 40 STATISTICAL SEGMENT TO WITNESS HIGHEST GROWTH RATE DURING FORECAST PERIOD
TABLE 49 MARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 50 MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
7.2 RULE-BASED
7.2.1 HIGH ACCURACY PROVIDED BY RULE-BASED NLP MODELS TO GAIN POPULARITY IN COMING YEARS
TABLE 51 RULE-BASED: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 52 RULE-BASED: MARKET, BY REGION, 2022–2027 (USD MILLION)
7.3 STATISTICAL
7.3.1 ADOPTION OF STATISTICAL NLP FOR SENTIMENT ANALYSIS AND INFORMATION EXTRACTION
TABLE 53 STATISTICAL: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 54 STATISTICAL: MARKET, BY REGION, 2022–2027 (USD MILLION)
7.4 HYBRID
7.4.1 HYBRID MODELS OFFER HIGH ACCURACY, BETTER SPEED, ROBUSTNESS, AND RELIABILITY
TABLE 55 HYBRID: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 56 HYBRID: MARKET, BY REGION, 2022–2027 (USD MILLION)
8 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY APPLICATION (Page No. - 123)
8.1 INTRODUCTION
8.1.1 APPLICATIONS: MARKET DRIVERS
FIGURE 41 AI CHATBOTS & VIRTUAL SCRIBE SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
TABLE 57 MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 58 MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
8.2 CLINICAL DECISION SUPPORT
TABLE 59 CLINICAL DECISION SUPPORT: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 60 CLINICAL DECISION SUPPORT: MARKET, BY REGION, 2022–2027 (USD MILLION)
8.3 DRUG DISCOVERY
TABLE 61 DRUG DISCOVERY: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 62 DRUG DISCOVERY: MARKET, BY REGION, 2022–2027 (USD MILLION)
8.4 CLINICAL TRIAL MATCHING
TABLE 63 CLINICAL TRIAL MATCHING: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 64 CLINICAL TRIAL MATCHING: MARKET, BY REGION, 2022–2027 (USD MILLION)
8.5 DICTATION & EMR IMPLICATIONS
TABLE 65 DICTATION & EMR IMPLICATIONS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 66 DICTATION & EMR IMPLICATIONS: MARKET, BY REGION, 2022–2027 (USD MILLION)
8.6 AUTOMATED REGISTRY REPORTING
TABLE 67 AUTOMATED REGISTRY REPORTING: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 68 AUTOMATED REGISTRY REPORTING: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
8.7 AI CHATBOTS & VIRTUAL SCRIBES
TABLE 69 AI CHATBOTS & VIRTUAL SCRIBE: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 70 AI CHATBOTS & VIRTUAL SCRIBE: MARKET, BY REGION, 2022–2027 (USD MILLION)
8.8 OTHER APPLICATIONS
TABLE 71 OTHER APPLICATIONS: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 72 OTHER APPLICATIONS: MARKET, BY REGION, 2022–2027 (USD MILLION)
9 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY DEPLOYMENT MODE (Page No. - 134)
9.1 INTRODUCTION
9.1.1 DEPLOYMENT MODES: MARKET DRIVERS
FIGURE 42 CLOUD SEGMENT TO WITNESS HIGHER CAGR DURING FORECAST PERIOD
TABLE 73 MARKET BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 74 MARKET BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
9.2 ON-PREMISES
TABLE 75 ON-PREMISES: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 76 ON-PREMISES: MARKET, BY REGION, 2022–2027 (USD MILLION)
9.3 CLOUD
TABLE 77 CLOUD: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 78 CLOUD: MARKET, BY REGION, 2022–2027 (USD MILLION)
10 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE (Page No. - 139)
10.1 INTRODUCTION
10.1.1 ORGANIZATION SIZE: MARKET DRIVERS
FIGURE 43 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
TABLE 79 MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 80 MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
10.2 LARGE ENTERPRISES
10.2.1 INTEGRATING DISPARATE DATA INTO MEANINGFUL SOURCES FOR AI ALGORITHMS
TABLE 81 LARGE ENTERPRISES: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 82 LARGE ENTERPRISES: MARKET, BY REGION, 2022–2027 (USD MILLION)
10.3 SMALL AND MEDIUM-SIZED ENTERPRISES
10.3.1 SMALL AND MEDIUM-SIZED ENTERPRISES ARE AT AN EARLY STAGE OF NLP ADOPTION ACROSS HEALTHCARE FIRMS
TABLE 83 SMALL AND MEDIUM-SIZED ENTERPRISES: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 84 SMALL AND MEDIUM-SIZED ENTERPRISES: MARKET, BY REGION, 2022–2027 (USD MILLION)
11 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TECHNIQUE (Page No. - 144)
11.1 INTRODUCTION
11.1.1 NLP TECHNIQUES: MARKET DRIVERS
FIGURE 44 SENTIMENT ANALYSIS SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
TABLE 85 MARKET BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 86 MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
11.2 OPTICAL CHARACTER RECOGNITION
TABLE 87 OCR: MARKET BY REGION, 2017–2021 (USD MILLION)
TABLE 88 OCR: MARKET BY REGION, 2022–2027 (USD MILLION)
11.3 INTERACTIVE VOICE RESPONSE
TABLE 89 IVR: MARKET BY REGION, 2017–2021 (USD MILLION)
TABLE 90 IVR: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
11.4 SENTIMENT ANALYSIS
TABLE 91 SENTIMENT ANALYSIS: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 92 SENTIMENT ANALYSIS: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
11.5 TEXT & SPEECH ANALYTICS
TABLE 93 TEXT & SPEECH ANALYTICS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 94 TEXT & SPEECH ANALYTICS: MARKET, BY REGION, 2022–2027 (USD MILLION)
11.6 IMAGE & PATTERN RECOGNITION
TABLE 95 IMAGE & PATTERN RECOGNITION: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 96 IMAGE & PATTERN RECOGNITION: MARKET, BY REGION, 2022–2027 (USD MILLION)
11.7 TEXT SUMMARIZATION & CATEGORIZATION
TABLE 97 TEXT SUMMARIZATION & CATEGORIZATION: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 98 TEXT SUMMARIZATION & CATEGORIZATION: MARKET, BY REGION, 2022–2027 (USD MILLION)
11.8 OTHER NLP TECHNIQUES
TABLE 99 OTHER NLP TECHNIQUES: MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 100 OTHER NLP TECHNIQUES: MARKET, BY REGION, 2022–2027 (USD MILLION)
12 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY END USER (Page No. - 156)
12.1 INTRODUCTION
12.1.1 END USERS: MARKET DRIVERS
FIGURE 45 PHARMACEUTICALS TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
TABLE 101 MARKET BY END USERS, 2017–2021 (USD MILLION)
TABLE 102 MARKET BY END USERS, 2022–2027 (USD MILLION)
12.2 PUBLIC HEALTH & GOVERNMENT AGENCIES
TABLE 103 PUBLIC HEALTH & GOVERNMENT AGENCIES: MARKET BY REGION, 2017–2021 (USD MILLION)
TABLE 104 PUBLIC HEALTH & GOVERNMENT AGENCIES: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
12.3 MEDICAL DEVICES
TABLE 105 MEDICAL DEVICES: MARKET SIZE, BY REGION, 2017–2021 (USD MILLION)
TABLE 106 MEDICAL DEVICES: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
12.4 HEALTHCARE INSURANCE
TABLE 107 HEALTHCARE INSURANCE: MARKET SIZE, BY REGION, 2017–2021 (USD MILLION)
TABLE 108 HEALTHCARE INSURANCE: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
12.5 PHARMACEUTICALS
TABLE 109 PHARMACEUTICALS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET SIZE, BY REGION, 2017–2021 (USD MILLION)
TABLE 110 PHARMACEUTICALS: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
12.6 OTHER END USERS
TABLE 111 OTHER END USERS: NCES MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 112 OTHER END USERS: MARKET SIZE, BY REGION, 2022–2027 (USD MILLION)
13 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION (Page No. - 165)
13.1 INTRODUCTION
13.1.1 REGIONS: MARKET DRIVERS
FIGURE 46 ASIA PACIFIC TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
FIGURE 47 INDIA TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
TABLE 113 MARKET, BY REGION, 2017–2021 (USD MILLION)
TABLE 114 MARKET, BY REGION, 2022–2027 (USD MILLION)
13.2 NORTH AMERICA
13.2.1 NORTH AMERICA: REGULATIONS
13.2.1.1 Gramm–Leach–Bliley Act
13.2.1.2 Federal Information Security Management Act
13.2.1.3 Health Insurance Portability and Accountability Act of 1996
13.2.1.4 Health Level Seven (HL7)
13.2.1.5 Occupational Safety and Health Administration (OSHA)
13.2.1.6 California Consumer Privacy Act (CSPA)
FIGURE 48 NORTH AMERICA: MARKET SNAPSHOT
TABLE 115 NORTH AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 116 NORTH AMERICA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 117 NORTH AMERICA: MARKET, BY SOLUTION, 2017–2021 (USD MILLION)
TABLE 118 NORTH AMERICA: MARKET, BY SOLUTION, 2022–2027 (USD MILLION)
TABLE 119 NORTH AMERICA: MARKET, BY SERVICE, 2017–2021 (USD MILLION)
TABLE 120 NORTH AMERICA: MARKET, BY SERVICE, 2022–2027 (USD MILLION)
TABLE 121 NORTH AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2017–2021 (USD MILLION)
TABLE 122 NORTH AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2022–2027 (USD MILLION)
TABLE 123 NORTH AMERICA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 124 NORTH AMERICA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 125 NORTH AMERICA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 126 NORTH AMERICA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
TABLE 127 NORTH AMERICA: MARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 128 NORTH AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
TABLE 129 NORTH AMERICA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 130 NORTH AMERICA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
TABLE 131 NORTH AMERICA: MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 132 NORTH AMERICA: MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
TABLE 133 NORTH AMERICA: MARKET, BY END USER, 2017–2021 (USD MILLION)
TABLE 134 NORTH AMERICA: MARKET, BY END USER, 2022–2027 (USD MILLION)
TABLE 135 NORTH AMERICA: MARKET, BY COUNTRY, 2017–2021 (USD MILLION)
TABLE 136 NORTH AMERICA: MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
13.2.2 US
13.2.2.1 Rapid adoption and use of innovative NLP solutions
TABLE 137 US: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 138 US: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 139 US: MARKET, BY SOLUTION, 2017–2021 (USD MILLION)
TABLE 140 US: MARKET, BY SOLUTION, 2022–2027 (USD MILLION)
TABLE 141 US: MARKET, BY SERVICE, 2017–2021 (USD MILLION)
TABLE 142 US: MARKET, BY SERVICE, 2022–2027 (USD MILLION)
TABLE 143 US: MARKET, BY PROFESSIONAL SERVICE, 2017–2021 (USD MILLION)
TABLE 144 US: MARKET, BY PROFESSIONAL SERVICE, 2022–2027 (USD MILLION)
TABLE 145 US: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 146 US: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 147 US: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 148 US: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
TABLE 149 US: MARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 150 US: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
TABLE 151 US: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 152 US: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
TABLE 153 US: MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 154 US: MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
TABLE 155 US: MARKET, BY END USER, 2017–2021 (USD MILLION)
TABLE 156 US: MARKET, BY END USER, 2022–2027 (USD MILLION)
13.2.3 CANADA
13.2.3.1 Favorable startup ecosystem to implement AI technologies
TABLE 157 CANADA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 158 CANADA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 159 CANADA: MARKET, BY SOLUTION, 2017–2021 (USD MILLION)
TABLE 160 CANADA: MARKET, BY SOLUTION, 2022–2027 (USD MILLION)
TABLE 161 CANADA: MARKET, BY SERVICE, 2017–2021 (USD MILLION)
TABLE 162 CANADA: MARKET, BY SERVICE, 2022–2027 (USD MILLION)
TABLE 163 CANADA: MARKET, BY PROFESSIONAL SERVICE, 2017–2021 (USD MILLION)
TABLE 164 CANADA: MARKET, BY PROFESSIONAL SERVICE, 2022–2027 (USD MILLION)
TABLE 165 CANADA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 166 CANADA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 167 CANADA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 168 CANADA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
TABLE 169 CANADA: NLPMARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 170 CANADA: MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
TABLE 171 CANADA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 172 CANADA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
TABLE 173 CANADA: MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 174 CANADA: MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
TABLE 175 CANADA: MARKET, BY END USER, 2017–2021 (USD MILLION)
TABLE 176 CANADA: MARKET, BY END USER, 2022–2027 (USD MILLION)
13.3 EUROPE
13.3.1 EUROPE: REGULATIONS
13.3.1.1 General Data Protection Regulation
13.3.1.2 European Committee for Standardization
13.3.1.3 European Technical Standards Institute
13.3.1.4 European Centre for Disease Prevention and Control
13.3.1.5 European Federation of Pharmaceutical Industries and Associations
TABLE 177 EUROPE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 178 EUROPE: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 179 EUROPE: MARKET, BY SOLUTION, 2017–2021 (USD MILLION)
TABLE 180 EUROPE: MARKET, BY SOLUTION, 2022–2027 (USD MILLION)
TABLE 181 EUROPE: MARKET, BY SERVICE, 2017–2021 (USD MILLION)
TABLE 182 EUROPE: MARKET, BY SERVICE, 2022–2027 (USD MILLION)
TABLE 183 EUROPE: MARKET, BY PROFESSIONAL SERVICE, 2017–2021 (USD MILLION)
TABLE 184 EUROPE: MARKET, BY PROFESSIONAL SERVICE, 2022–2027 (USD MILLION)
TABLE 185 EUROPE: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 186 EUROPE: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 187 EUROPE: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 188 EUROPE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
TABLE 189 EUROPE: MARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 190 EUROPE: MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
TABLE 191 EUROPE: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 192 EUROPE: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
TABLE 193 EUROPE: MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 194 EUROPE: MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
TABLE 195 EUROPE: MARKET, BY END USER, 2017–2021 (USD MILLION)
TABLE 196 EUROPE: MARKET, BY END USER, 2022–2027 (USD MILLION)
TABLE 197 EUROPE: MARKET, BY COUNTRY, 2017–2021 (USD MILLION)
TABLE 198 EUROPE: MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
13.3.2 UK
13.3.2.1 Increasing usage of online platforms to help healthcare companies manage patient queries efficiently
TABLE 199 UK: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 200 UK: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 201 UK: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 202 UK: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 203 UK: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 204 UK: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.3.3 GERMANY
13.3.3.1 Growing digital mobility and digital spending across the healthcare industry
TABLE 205 GERMANY: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 206 GERMANY: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 207 GERMANY: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 208 GERMANY: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 209 GERMANY: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 210 GERMANY: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.3.4 FRANCE
13.3.4.1 Growing concerns of NLP vendors over managing clinical data due to digital transformation
TABLE 211 FRANCE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 212 FRANCE: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 213 FRANCE: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 214 FRANCE: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 215 FRANCE: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 216 FRANCE: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.3.4.2 REST OF EUROPE
TABLE 217 REST OF EUROPE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 218 REST OF EUROPE: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 219 REST OF EUROPE: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 220 REST OF EUROPE: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 221 REST OF EUROPE: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 222 REST OF EUROPE: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.4 ASIA PACIFIC
13.4.1 ASIA PACIFIC: REGULATIONS
13.4.1.1 Personal Data Protection Act
13.4.1.2 International Organization for Standardization 27001
13.4.1.3 Act on the Protection of Personal Information
13.4.1.4 Critical Information Infrastructure
FIGURE 49 ASIA PACIFIC: MARKET SNAPSHOT
TABLE 223 ASIA PACIFIC: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 224 ASIA PACIFIC: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 225 ASIA PACIFIC: MARKET, BY SOLUTION, 2017–2021 (USD MILLION)
TABLE 226 ASIA PACIFIC: MARKET, BY SOLUTION, 2022–2027 (USD MILLION)
TABLE 227 ASIA PACIFIC: MARKET, BY SERVICE, 2017–2021 (USD MILLION)
TABLE 228 ASIA PACIFIC: MARKET, BY SERVICE, 2022–2027 (USD MILLION)
TABLE 229 ASIA PACIFIC: MARKET, BY PROFESSIONAL SERVICE, 2017–2021 (USD MILLION)
TABLE 230 ASIA PACIFIC: MARKET, BY PROFESSIONAL SERVICE, 2022–2027 (USD MILLION)
TABLE 231 ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 232 ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 233 ASIA PACIFIC: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 234 ASIA PACIFIC: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
TABLE 235 ASIA PACIFIC: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 236 ASIA PACIFIC: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
TABLE 237 ASIA PACIFIC: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 238 ASIA PACIFIC: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
TABLE 239 ASIA PACIFIC: MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 240 ASIA PACIFIC: MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
TABLE 241 ASIA PACIFIC: MARKET, BY END USER, 2017–2021 (USD MILLION)
TABLE 242 ASIA PACIFIC: MARKET, BY END USER, 2022–2027 (USD MILLION)
TABLE 243 ASIA PACIFIC: MARKET, BY COUNTRY, 2017–2021 (USD MILLION)
TABLE 244 ASIA PACIFIC: MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
13.4.2 CHINA
13.4.2.1 Growing need to manage huge amount of clinical data efficiently
TABLE 245 CHINA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 246 CHINA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 247 CHINA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 248 CHINA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 249 CHINA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 250 CHINA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.4.3 JAPAN
13.4.3.1 Growing adoption of AI and NLP technologies to handle patient data
TABLE 251 JAPAN: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 252 JAPAN: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 253 JAPAN: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 254 JAPAN: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 255 JAPAN: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 256 JAPAN: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.4.4 INDIA
13.4.4.1 Increasing government initiatives and innovative technologies to fuel the demand
TABLE 257 INDIA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 258 INDIA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 259 INDIA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 260 INDIA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 261 INDIA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 262 INDIA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.4.4.2 Rest of Asia Pacific
TABLE 263 REST OF ASIA PACIFIC: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 264 REST OF ASIA PACIFIC: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 265 REST OF ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 266 REST OF ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 267 REST OF ASIA PACIFIC: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 268 REST OF ASIA PACIFIC: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.5 MIDDLE EAST AND AFRICA
13.5.1 MIDDLE EAST AND AFRICA: REGULATIONS
13.5.1.1 UAE Ministry of Health
13.5.1.2 Health Authority - Abu Dhabi
13.5.1.3 Dubai Health Authority
13.5.1.4 Federal Law No. 2 of 2019 (Health Data Law)
13.5.1.5 Israeli Privacy Protection Regulations (Data Security), 5777-2017
13.5.1.6 Applicability of the GDPR in companies from the KSA
13.5.1.7 Protection of Personal Information Act
TABLE 269 MIDDLE EAST AND AFRICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 270 MIDDLE EAST AND AFRICA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 271 MIDDLE EAST AND AFRICA: MARKET, BY SOLUTION, 2017–2021 (USD MILLION)
TABLE 272 MIDDLE EAST AND AFRICA: MARKET, BY SOLUTION, 2022–2027 (USD MILLION)
TABLE 273 MIDDLE EAST AND AFRICA: MARKET, BY SERVICE, 2017–2021 (USD MILLION)
TABLE 274 MIDDLE EAST AND AFRICA: MARKET, BY SERVICE, 2022–2027 (USD MILLION)
TABLE 275 MIDDLE EAST AND AFRICA: MARKET, BY PROFESSIONAL SERVICE, 2017–2021 (USD MILLION)
TABLE 276 MIDDLE EAST AND AFRICA: MARKET, BY PROFESSIONAL SERVICE, 2022–2027 (USD MILLION)
TABLE 277 MIDDLE EAST AND AFRICA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 278 MIDDLE EAST AND AFRICA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 279 MIDDLE EAST AND AFRICA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 280 MIDDLE EAST AND AFRICA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
TABLE 281 MIDDLE EAST AND AFRICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 282 MIDDLE EAST AND AFRICA: MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
TABLE 283 MIDDLE EAST AND AFRICA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 284 MIDDLE EAST AND AFRICA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
TABLE 285 MIDDLE EAST AND AFRICA: MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 286 MIDDLE EAST AND AFRICA: MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
TABLE 287 MIDDLE EAST AND AFRICA: MARKET, BY END USER, 2017–2021 (USD MILLION)
TABLE 288 MIDDLE EAST AND AFRICA: MARKET, BY END USER, 2022–2027 (USD MILLION)
TABLE 289 MIDDLE EAST AND AFRICA: MARKET, BY COUNTRY, 2017–2021 (USD MILLION)
TABLE 290 MIDDLE EAST AND AFRICA: NLPMARKET, BY COUNTRY, 2022–2027 (USD MILLION)
13.5.2 SAUDI ARABIA
13.5.2.1 Increasing initiatives by government and private sectors for technological adoption to drive market growth
TABLE 291 SAUDI ARABIA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 292 SAUDI ARABIA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 293 SAUDI ARABIA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 294 SAUDI ARABIA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 295 SAUDI ARABIA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 296 SAUDI ARABIA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.5.3 UAE
13.5.3.1 Growing investments in AI tools and technologies in healthcare sector to support market growth
TABLE 297 UAE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 298 UAE: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 299 UAE: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 300 UAE: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 301 UAE: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 302 UAE: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.5.4 SOUTH AFRICA
13.5.4.1 Growing digitalization offers opportunities for NLP in healthcare and life sciences market
TABLE 303 SOUTH AFRICA: MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 304 SOUTH AFRICA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 305 SOUTH AFRICA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 306 SOUTH AFRICA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 307 SOUTH AFRICA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 308 SOUTH AFRICA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.5.5 REST OF MIDDLE EAST AND AFRICA
TABLE 309 REST OF MIDDLE EAST AND AFRICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 310 REST OF MIDDLE EAST AND AFRICA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 311 REST OF MIDDLE EAST AND AFRICA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 312 REST OF MIDDLE EAST AND AFRICA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 313 REST OF MIDDLE EAST AND AFRICA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 314 REST OF MIDDLE EAST AND AFRICA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.6 LATIN AMERICA
13.6.1 LATIN AMERICA: REGULATIONS
13.6.1.1 General Health Law
13.6.1.2 ANVISA - Brazil National Health Surveillance Agency
13.6.1.3 Brazil Data Protection Law
13.6.1.4 Argentina Personal Data Protection Law No. 25.326
TABLE 315 LATIN AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 316 LATIN AMERICA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 317 LATIN AMERICA: MARKET, BY SOLUTION, 2017–2021 (USD MILLION)
TABLE 318 LATIN AMERICA: MARKET, BY SOLUTION, 2022–2027 (USD MILLION)
TABLE 319 LATIN AMERICA: MARKET, BY SERVICE, 2017–2021 (USD MILLION)
TABLE 320 LATIN AMERICA: MARKET, BY SERVICE, 2022–2027 (USD MILLION)
TABLE 321 LATIN AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2017–2021 (USD MILLION)
TABLE 322 LATIN AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2022–2027 (USD MILLION)
TABLE 323 LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 324 LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 325 LATIN AMERICA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 326 LATIN AMERICA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
TABLE 327 LATIN AMERICA: MARKET, BY NLP TYPE, 2017–2021 (USD MILLION)
TABLE 328 LATIN AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE, 2022–2027 (USD MILLION)
TABLE 329 LATIN AMERICA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2017–2021 (USD MILLION)
TABLE 330 LATIN AMERICA: NATURAL LANGUAGE PROCESSING MARKET, BY NLP TECHNIQUE, 2022–2027 (USD MILLION)
TABLE 331 LATIN AMERICA: MARKET, BY APPLICATION, 2017–2021 (USD MILLION)
TABLE 332 LATIN AMERICA: MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
TABLE 333 LATIN AMERICA: MARKET, BY END USER, 2017–2021 (USD MILLION)
TABLE 334 LATIN AMERICA: MARKET, BY END USER, 2022–2027 (USD MILLION)
TABLE 335 LATIN AMERICA: MARKET, BY COUNTRY, 2017–2021 (USD MILLION)
TABLE 336 LATIN AMERICA: MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
13.6.2 BRAZIL
13.6.2.1 Increased number of healthcare regulatory bodies to promote investment and penetration
TABLE 337 BRAZIL: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 338 BRAZIL: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 339 BRAZIL: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 340 BRAZIL: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 341 BRAZIL: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 342 BRAZIL: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.6.3 MEXICO
13.6.3.1 Development of new technology policies and increasing AI investments to boost market growth
TABLE 343 MEXICO: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 344 MEXICO: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 345 MEXICO: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 346 MEXICO: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 347 MEXICO: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 348 MEXICO: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
13.6.4 REST OF LATIN AMERICA
TABLE 349 REST OF LATIN AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2021 (USD MILLION)
TABLE 350 REST OF LATIN AMERICA: MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
TABLE 351 REST OF LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2017–2021 (USD MILLION)
TABLE 352 REST OF LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
TABLE 353 REST OF LATIN AMERICA: MARKET, BY ORGANIZATION SIZE, 2017–2021 (USD MILLION)
TABLE 354 REST OF LATIN AMERICA: MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
14 COMPETITIVE LANDSCAPE (Page No. - 253)
14.1 OVERVIEW
14.2 KEY PLAYER STRATEGIES
TABLE 355 OVERVIEW OF STRATEGIES ADOPTED BY KEY NLP VENDORS
14.3 REVENUE ANALYSIS
14.3.1 HISTORICAL REVENUE ANALYSIS
FIGURE 50 HISTORICAL REVENUE ANALYSIS OF TOP FIVE LEADING PLAYERS, 2019–2021 (USD MILLION)
14.4 MARKET SHARE ANALYSIS
FIGURE 51 MARKET SHARE ANALYSIS FOR KEY COMPANIES
TABLE 356 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: DEGREE OF COMPETITION
14.5 MARKET EVALUATION FRAMEWORK
FIGURE 52 MARKET EVALUATION FRAMEWORK: EXPANSIONS AND CONSOLIDATIONS IN MARKET BETWEEN 2020–2022
14.6 COMPANY EVALUATION QUADRANT
14.6.1 STARS
14.6.2 EMERGING LEADERS
14.6.3 PERVASIVE PLAYERS
14.6.4 PARTICIPANTS
FIGURE 53 MARKET: COMPANY EVALUATION QUADRANT, 2022
14.7 COMPETITIVE BENCHMARKING
14.7.1 COMPANY PRODUCT FOOTPRINT
FIGURE 54 PRODUCT PORTFOLIO ANALYSIS OF TOP PLAYERS IN NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 55 BUSINESS STRATEGY EXCELLENCE OF TOP PLAYERS IN MARKET
TABLE 357 MARKET: COMPETITIVE BENCHMARKING OF TOP 10 KEY PLAYERS
14.8 STARTUP/SME EVALUATION QUADRANT
14.8.1 PROGRESSIVE COMPANIES
14.8.2 RESPONSIVE COMPANIES
14.8.3 DYNAMIC COMPANIES
14.8.4 STARTING BLOCKS
FIGURE 56 MARKET, STARTUP/SME EVALUATION QUADRANT
14.9 STARTUP/SME COMPETITIVE BENCHMARKING
14.9.1 COMPANY PRODUCT FOOTPRINT
FIGURE 57 PRODUCT PORTFOLIO ANALYSIS OF STARTUP/SME IN NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 58 BUSINESS STRATEGY EXCELLENCE OF STARTUP/SME IN MARKET
TABLE 358 MARKET: COMPETITIVE BENCHMARKING OF STARTUP/SMES
TABLE 359 MARKET: DETAILED LIST OF KEY STARTUPS/SMES
14.10 COMPETITIVE SCENARIO AND TRENDS
14.10.1 NEW PRODUCT LAUNCHES
TABLE 360 NEW SERVICE/PRODUCT LAUNCHES, 2019–2022
14.10.2 DEALS
TABLE 361 DEALS, 2019–2022
15 COMPANY PROFILES (Page No. - 275)
15.1 INTRODUCTION
(Business overview, Products/Solutions/Services offered, Recent developments & MnM View)*
15.2 KEY PLAYERS
15.2.1 IBM
TABLE 362 IBM: BUSINESS OVERVIEW
FIGURE 59 IBM: COMPANY SNAPSHOT
TABLE 363 IBM: SOLUTIONS AND SERVICES OFFERED
TABLE 364 IBM: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 365 IBM: DEALS
15.2.2 MICROSOFT
TABLE 366 MICROSOFT: BUSINESS OVERVIEW
FIGURE 60 MICROSOFT: COMPANY SNAPSHOT
TABLE 367 MICROSOFT: SOLUTIONS AND SERVICES OFFERED
TABLE 368 MICROSOFT: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 369 MICROSOFT: DEALS
15.2.3 GOOGLE
TABLE 370 GOOGLE: BUSINESS OVERVIEW
FIGURE 61 GOOGLE: COMPANY SNAPSHOT
TABLE 371 GOOGLE: SOLUTIONS OFFERED
TABLE 372 GOOGLE: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 373 GOOGLE: DEALS
15.2.4 AWS
TABLE 374 AWS: BUSINESS OVERVIEW
FIGURE 62 AWS: COMPANY SNAPSHOT
TABLE 375 AWS: SOLUTIONS OFFERED
TABLE 376 AWS: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 377 AWS: DEALS
15.2.5 IQVIA
TABLE 378 IQVIA: BUSINESS OVERVIEW
FIGURE 63 IQVIA: COMPANY SNAPSHOT
TABLE 379 IQVIA: SOLUTIONS OFFERED
TABLE 380 IQVIA: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 381 IQVIA: DEALS
15.2.6 ORACLE
TABLE 382 ORACLE: BUSINESS OVERVIEW
FIGURE 64 ORACLE: COMPANY SNAPSHOT
TABLE 383 ORACLE: SOLUTIONS AND SERVICES OFFERED
TABLE 384 ORACLE: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 385 ORACLE: DEALS
15.2.7 INOVALON
TABLE 386 INOVALON: BUSINESS OVERVIEW
TABLE 387 INOVALON: SOLUTIONS AND SERVICES OFFERED
TABLE 388 INOVALON: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 389 INOVALON: DEALS
15.2.8 DOLBEY
TABLE 390 DOLBEY: BUSINESS OVERVIEW
TABLE 391 DOLBEY: SOLUTIONS OFFERED
TABLE 392 DOLBEY: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 393 DOLBEY: DEALS
15.2.9 AVERBIS
TABLE 394 AVERBIS: BUSINESS OVERVIEW
TABLE 395 AVERBIS: SOLUTIONS OFFERED
TABLE 396 AVERBIS: PRODUCT LAUNCHES AND ENHANCEMENTS
15.2.10 SAS INSTITUTE
TABLE 397 SAS INSTITUTE: BUSINESS OVERVIEW
FIGURE 65 SAS INSTITUTE: COMPANY SNAPSHOT
TABLE 398 SAS INSTITUTE: SOLUTIONS OFFERED
TABLE 399 SAS INSTITUTE: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 400 SAS INSTITUTE: DEALS
*Details on Business overview, Products/Solutions/Services offered, Recent developments & MnM View might not be captured in case of unlisted companies.
15.3 OTHER KEY PLAYERS
15.3.1 PRESS GANEY
15.3.2 ELLIPSIS HEALTH
15.3.3 HEALTH FIDELITY
15.3.4 LEXALYTICS
15.3.5 CENTENE
15.3.6 CAPTION HEALTH
15.3.7 CLINITHINK
15.3.8 HPE
15.3.9 ONCORA MEDICAL
15.3.10 FLATIRON HEALTH
15.3.11 APIXIO
15.4 STARTUP OR SMES
15.4.1 FORESEE MEDICAL
15.4.2 GNANI.AI
15.4.3 NOTABLE
15.4.4 BIOFOURMIS
15.4.5 SUKI
15.4.6 WAVE HEALTH TECHNOLOGIES
15.4.7 CORTI
15.4.8 CLOUDMEDX
15.4.9 MEDINREAL
15.4.10 EMTELLIGENT
16 ADJACENT AND RELATED MARKETS (Page No. - 321)
16.1 INTRODUCTION
16.2 NLP MARKET - GLOBAL FORECAST TO 2027
16.2.1 MARKET DEFINITION
16.2.2 MARKET OVERVIEW
16.2.2.1 NLP market, by component
TABLE 401 NATURAL LANGUAGE PROCESSING MARKET, BY COMPONENT, 2016–2021 (USD MILLION)
TABLE 402 NATURAL LANGUAGE PROCESSING MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
16.2.2.2 NLP market, by type
TABLE 403 NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2016–2021 (USD MILLION)
TABLE 404 NATURAL LANGUAGE PROCESSING MARKET, BY TYPE, 2022–2027 (USD MILLION)
16.2.2.3 NLP market, by deployment mode
TABLE 405 NATURAL LANGUAGE PROCESSING MARKET, BY DEPLOYMENT MODE, 2016–2021 (USD MILLION)
TABLE 406 NATURAL LANGUAGE PROCESSING MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
16.2.2.4 NLP market, by organization size
TABLE 407 NATURAL LANGUAGE PROCESSING MARKET, BY ORGANIZATION SIZE, 2016–2021 (USD MILLION)
TABLE 408 NATURAL LANGUAGE PROCESSING MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
16.2.2.5 NLP market, by application
TABLE 409 NATURAL LANGUAGE PROCESSING MARKET, BY APPLICATION, 2016–2021 (USD MILLION)
TABLE 410 NATURAL LANGUAGE PROCESSING MARKET, BY APPLICATION, 2022–2027 (USD MILLION)
16.2.2.6 NLP market, by technology
TABLE 411 NATURAL LANGUAGE PROCESSING MARKET, BY TECHNOLOGY, 2016–2021 (USD MILLION)
TABLE 412 NATURAL LANGUAGE PROCESSING MARKET, BY TECHNOLOGY, 2022–2027 (USD MILLION)
16.2.2.7 NLP market, by vertical
TABLE 413 NATURAL LANGUAGE PROCESSING MARKET, BY VERTICAL, 2016–2021 (USD MILLION)
TABLE 414 NATURAL LANGUAGE PROCESSING MARKET, BY VERTICAL, 2022–2027 (USD MILLION)
16.2.2.8 NLP market, by region
TABLE 415 NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2016–2021 (USD MILLION)
TABLE 416 NATURAL LANGUAGE PROCESSING MARKET, BY REGION, 2022–2027 (USD MILLION)
16.3 CHATBOT MARKET - GLOBAL FORECAST TO 2026
16.3.1 MARKET DEFINITION
16.3.2 MARKET OVERVIEW
16.3.2.1 Chatbot market, by component
TABLE 417 CHATBOT MARKET, BY COMPONENT, 2015–2019 (USD MILLION)
TABLE 418 CHATBOT MARKET, BY COMPONENT, 2020–2026 (USD MILLION)
16.3.2.2 Chatbot market, by type
TABLE 419 CHATBOT MARKET, BY TYPE, 2015–2019 (USD MILLION)
TABLE 420 CHATBOT MARKET, BY TYPE, 2020–2026 (USD MILLION)
16.3.2.3 Chatbot market, by deployment mode
TABLE 421 CHATBOT MARKET, BY DEPLOYMENT MODE, 2015–2019 (USD MILLION)
TABLE 422 CHATBOT MARKET, BY DEPLOYMENT MODE, 2020–2026 (USD MILLION)
16.3.2.4 Chatbot market, by channel integration
TABLE 423 CHATBOT MARKET, BY CHANNEL INTEGRATION, 2015–2019 (USD MILLION)
TABLE 424 CHATBOT MARKET, BY CHANNEL INTEGRATION, 2020–2026 (USD MILLION)
16.3.2.5 Chatbot market, by business function
TABLE 425 CHATBOT MARKET, BY BUSINESS FUNCTION, 2015–2019 (USD MILLION)
TABLE 426 CHATBOT MARKET, BY BUSINESS FUNCTION, 2020–2026 (USD MILLION)
16.3.2.6 Chatbot market, by application
TABLE 427 CHATBOT MARKET, BY APPLICATION, 2015–2019 (USD MILLION)
TABLE 428 CHATBOT MARKET, BY APPLICATION, 2020–2026 (USD MILLION)
16.3.2.7 Chatbot market, by vertical
TABLE 429 CHATBOT MARKET, BY VERTICAL, 2015–2019 (USD MILLION)
TABLE 430 CHATBOT MARKET, BY VERTICAL, 2020–2026 (USD MILLION)
16.3.2.8 Chatbot market, by region
TABLE 431 CHATBOT MARKET, BY REGION, 2015–2019 (USD MILLION)
TABLE 432 CHATBOT MARKET, BY REGION, 2020–2026 (USD MILLION)
17 APPENDIX (Page No. - 336)
17.1 INDUSTRY EXPERTS
17.2 DISCUSSION GUIDE
17.3 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
17.4 CUSTOMIZATION OPTIONS
17.5 RELATED REPORTS
17.6 AUTHOR DETAILS
This research study involved the extensive use of secondary sources, directories, and databases such as Dun & Bradstreet (D&B) Hoovers, and Bloomberg BusinessWeek to identify and collect information useful for a technical, market-oriented, and commercial study of the NLP in healthcare and life sciences market. The primary sources were mainly industry experts from the core and related industries and preferred suppliers, manufacturers, distributors, service providers, technology developers, alliances, and organizations related to all segments of the value chain of this market. In-depth interviews were conducted with various primary respondents that included key industry participants, subject matter experts, C-level executives of key market players, and industry consultants to obtain and verify critical qualitative and quantitative information. The following illustrative figure shows the market research methodology applied in making this report on the market.
Secondary Research
The market for companies offering frontline workers training for different verticals was estimated and projected based on the secondary data made available through paid and unpaid sources and by analyzing their product portfolios in the ecosystem of the NLP in healthcare and life sciences market. It also involved rating products of companies based on their performance and quality. In the secondary research process, various sources were referred to for identifying and collecting information for this study on the market. The secondary sources included annual reports, press releases and investor presentations of companies, white papers, journals, and certified publications and articles by recognized authors, directories, and databases.
Secondary research was mainly used to obtain key information about the supply chain of the market, the total pool of key players, market classification, and segmentation according to industry trends to the bottommost level, regional markets, and key developments from both, market and technology-oriented perspectives that were further validated by primary sources.
Primary Research
In the primary research process, various sources from both, the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side included industry experts such as Chief Executive Officers (CEOs), Chief Technology Officers (CTOs), Chief Operating Officers (COOs), Vice Presidents (VPs), Managing Directors (MDs), technology and innovation directors, and related key executives from different key companies and organizations operating in the NLP in healthcare and life sciences market.
The following is the breakup of primary profiles:
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
In this approach for market estimation, the key frontline workers training vendors, such as IBM (US), Microsoft (US), Google (US), AWS (US), IQVIA (US), Oracle (US), Inovalon(US), Dolbey (US), Averbis (Germany), SAS Institute (US), Press Ganey (US), Ellipsis Health (US), Health Fidelity (US), Centene (US), Caption Health (US), Clinithink (US), HPE (US), Oncora Medical (US), Flatiron Health (US), Apixio (US), Forsee Medical (US), Gnani.ai (India), Notable (US), Biofourmis (US), Suki (US), Wave Health Technologies (US), Corti (Denmark), CloudMedx (US), MedlnReal (US), Emtelligent (US) contribute almost 60-65% to the global NLP in healthcare and life sciences market. After confirming these companies through primary interviews with industry experts, their total revenue through annual reports, Securities and Exchange Commission (SEC) filings, and paid databases was estimated. These companies’ revenue pertaining to the Business Units (BUs) that offer frontline workers training was identified through similar sources. Then through primaries, the data of revenue generated was collected through specific frontline workers training. The collective revenue of key companies that offer frontline workers training comprises 60%–65% of the market, which was again confirmed through primary interviews with industry experts. With the assumption that the rest of the market is contributed by smaller players (part of the unorganized market), the market size of organized players (55%–60%) and unorganized players (40%–45%) collectively was assumed to be the market size of the global NLP in healthcare and life sciences market for Financial Year (FY) 2022.
- The pricing trend is assumed to vary over time.
- All the forecasts are made with the standard assumption that the accepted currency is USD.
- For the conversion of various currencies to USD, average historical exchange rates are used according to the year specified. For all the historical and current exchange rates required for calculations and currency conversions, the US Internal Revenue Service's website is used.
- All the forecasts are made under the standard assumption that the globally accepted currency USD remains constant during the next five years.
- Vendor-side analysis: The market size estimates of associated solutions and services are factored in from the vendor side by assuming an average of licensing and subscription-based models of leading and innovative vendors in the market.
Demand/end-user analysis: End users operating in verticals across regions are analyzed in terms of market spending on frontline workers training based on some of the key use cases. These factors for the frontline workers training industry per region are separately analyzed, and the average spending was extrapolated with an approximation based on assumed weightage. This factor is derived by averaging various market influencers, including recent developments, regulations, mergers and acquisitions, enterprise/SME adoption, startup ecosystem, IT spending, technology propensity and maturity, use cases, and the estimated number of organizations per region.
Data Triangulation
After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Report Objectives
- To define, describe, and predict the NLP in healthcare and life sciences market by component, organization size, NLP type, application, deployment mode, integrated technology, end user, and region
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America
- To profile key players and comprehensively analyze their market rankings and core competencies
- To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the NLP in healthcare and life sciences market
NLP Healthcare Market & Its impact on NLP in Healthcare and Life Sciences Market
The NLP Healthcare Market and NLP in Healthcare and Life Sciences Market are closely related. The NLP healthcare market refers to the market for natural language processing technologies and solutions specifically in the healthcare industry. This includes NLP solutions for tasks such as clinical documentation, voice recognition, and chatbots.
On the other hand, the NLP in Healthcare and Life Sciences Market refers to the broader application of natural language processing technologies and solutions in the healthcare and life sciences industries. This includes the use of NLP for tasks such as drug discovery, clinical trial management, and disease surveillance.
While there is some overlap between these two markets, they are distinct and have different areas of focus. The NLP healthcare market is primarily concerned with improving healthcare delivery and patient outcomes, while the NLP in healthcare and life sciences market is focused on driving innovation and advancements in the healthcare and life sciences industries as a whole.
The NLP healthcare market is expected to have a significant impact on the NLP in healthcare and life sciences market. This is because the NLP healthcare market is a subset of the broader NLP in healthcare and life sciences market, and advances in NLP technology in the healthcare industry can lead to new opportunities for NLP in other areas of healthcare and life sciences.
One of the primary ways that the NLP healthcare market is expected to impact the NLP in healthcare and life sciences market is through increased investment in NLP technology and solutions.
The NLP healthcare market can act as a catalyst for the adoption of NLP technology in other areas of healthcare and life sciences. As more healthcare providers and organizations adopt NLP technology for tasks such as clinical documentation and voice recognition, it can create a demand for similar solutions in other areas of healthcare and life sciences.
Overall, the NLP healthcare market is expected to have a positive impact on the NLP in healthcare and life sciences market by driving innovation, increasing investment, and creating new opportunities for NLP technology in other areas of healthcare and life sciences.
Futuristic growth use-cases of NLP Healthcare Market
- Personalized Medicine: NLP can help healthcare providers to better understand patient needs and preferences, which can lead to the development of more personalized treatment plans. NLP can analyze patient data from various sources, such as electronic health records, patient feedback, and social media, to identify patterns and trends that can help inform treatment decisions.
- Drug Discovery: NLP can be used to analyze large volumes of scientific literature and data to identify potential drug targets and to accelerate drug discovery. This can help pharmaceutical companies to identify new drug candidates more quickly and efficiently.
- Patient Engagement: NLP can be used to develop chatbots and virtual assistants that can interact with patients and provide personalized health information and guidance. This can help patients to better manage their health and to stay engaged in their treatment.
- Medical Image Analysis: NLP can be used to analyze medical images and to extract valuable insights that can help healthcare providers to diagnose and treat patients more accurately. This can include analyzing images for signs of disease, identifying abnormalities, and tracking disease progression over time.
- Clinical Decision Support: NLP can be used to develop clinical decision support systems that can help healthcare providers to make more informed treatment decisions. This can include analyzing patient data to identify potential drug interactions, to provide dosing recommendations, and to suggest alternative treatment options.
Overall, the growth potential for NLP in the healthcare industry is significant, and there are many exciting use-cases that are being explored. As NLP technology continues to evolve, it is likely that we will see new and innovative applications in the healthcare industry in the years to come.
Some of the top companies in NLP Healthcare Market are Cerner Corporation, IBM Corporation, Nuance Communications, 3M Health Information Systems, Health Fidelity, Linguamatics
Industries Getting Impacted in the future by NLP Healthcare Market
- Healthcare: The healthcare industry is the primary industry that is being impacted by the NLP healthcare market. NLP technology is being used to improve clinical documentation, patient engagement, and clinical decision-making, among other things.
- Pharmaceutical and Life Sciences: The pharmaceutical and life sciences industries are also being impacted by the NLP healthcare market. NLP technology is being used to accelerate drug discovery, analyze medical literature, and identify potential drug targets.
- Insurance: The insurance industry is likely to be impacted by the NLP healthcare market as well. NLP technology is being used to identify high-risk patients and to improve risk adjustment and coding accuracy, which can help insurers to better manage costs and improve outcomes.
- Telemedicine: The telemedicine industry is another industry that is likely to be impacted by the NLP healthcare market. NLP technology can be used to improve the accuracy of virtual consultations and to provide personalized health information to patients.
- Retail and Consumer Goods: The retail and consumer goods industries are also being impacted by the NLP healthcare market. NLP technology can be used to analyze consumer feedback and social media data to identify trends and preferences related to health and wellness.
Available Customizations
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Product Analysis
- Product matrix provides a detailed comparison of the product portfolio of each company
Geographic Analysis
- Further breakup of the North American NLP in healthcare and life sciences market
- Further breakup of the European market
- Further breakup of the Asia Pacific market
- Further breakup of the Latin American market
- Further breakup of the Middle East and Africa market
Company Information
- Detailed analysis and profiling of additional market players up to 5
Generating Response ...
Growth opportunities and latent adjacency in NLP in Healthcare and Life Sciences Market
Understand the application of NLP in Healthcare.
Detailed understanding of the Artificial Intelligence (Data Scientist, Machine Learning, NLP, Sentiment Analysis, Recommender Systems).