세계의 의료 및 생명과학용 NLP 시장 규모 : NLP 기법별, 용도별 - 예측(-2030년)

The NLP in healthcare & life sciences market is expanding rapidly, with a projected market size rising from USD 5.18 billion in 2025 to USD 16.01 billion by 2030, at a CAGR of 25.3% during the forecast period. The substantial increase in unstructured clinical data, including electronic health records, physician notes, and pathology reports, drives the demand for NLP technologies to derive actionable insights. Simultaneously, clinical decision support is gaining importance, with NLP enabling real-time diagnostics and treatment recommendations in precision medicine. However, outdated IT systems can be incompatible with modern NLP tools, posing integration and interoperability challenges. As healthcare systems modernize, NLP is poised to become a cornerstone of data-driven, personalized care delivery.

"NLG type segment to account for the fastest growth rate during the forecast period"

Natural language generation (NLG) is the fastest-growing segment in the NLP in healthcare and life sciences market. NLG transforms structured clinical data into clear, human-like narratives, improving clinical documentation and reducing physician workload. It automates the creation of patient summaries, discharge notes, and personalized communications, enhancing patient engagement and adherence to treatment. The rising need for efficient data handling and automation in healthcare drives NLG adoption. As healthcare providers focus on improving operational efficiency and patient outcomes, NLG becomes a critical tool for enabling scalable, accurate, and timely clinical documentation and communication within the NLP in healthcare and life sciences market.

"Named entity recognition (NER) NLP technique segment to hold the largest market share during the forecast period"

Named entity recognition (NER) holds the largest market share in NLP in healthcare and life sciences because it is critical in extracting structured information from unstructured medical texts. NER enhances clinical decision-making, medical coding, and data interoperability by identifying and classifying key entities such as diseases, drugs, procedures, and patient information. Its ability to accurately process large volumes of electronic health records, clinical trial data, and biomedical literature makes it essential for improving diagnostics, treatment planning, and research. As healthcare increasingly relies on data-driven insights, NER's precision and scalability make it a foundational tool across multiple healthcare applications.

"North America leads with advanced infrastructure and early tech adoption, while Asia Pacific records fastest growth with digitalization and government AI initiatives"

North America leads the NLP in healthcare and life sciences market due to its advanced healthcare IT infrastructure, strong regulatory support for digital health, and early adoption of electronic health records and AI. The region is home to key industry players and research institutions that actively develop and deploy NLP applications for clinical decision-making, patient monitoring, and administrative automation. Meanwhile, Asia Pacific is the fastest-growing market, driven by rapid digitization of healthcare systems, increasing investments in AI, and growing awareness of personalized medicine. China, India, and Japan prioritize healthcare modernization, with government initiatives encouraging AI integration. The region's rising healthcare demands and technological advancements make it a hotspot for NLP adoption in the coming years.

Breakdown of Primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the NLP in healthcare & life sciences market.

• By Company: Tier I - 35%, Tier II - 45%, and Tier III - 20%
• By Designation: C-Level Executives - 35%, D-Level Executives -25%, and others - 40%
• By Region: North America - 40%, Europe - 30%, Asia Pacific - 20%, Middle East & Africa - 5%, and Latin America - 5%

The report includes a study of key players offering NLP in healthcare & life sciences. It profiles major vendors in the NLP in healthcare & life sciences market. The major market players include Microsoft (US), Google (US), IBM (US), AWS (US), IQVIA (US), Oracle (US), Inovalon (US), Dolbey Systems (US), Averbis (Germany), SAS Institute (US), Solventum (US), Press Ganey (US), Ellipsis Health (US), Lexalytics (US), NVIDIA (US), GE Healthcare (US), Clinithink (US), HPE (US), Oncora Medical (US), Flatiron Health (US), Datavant (US), Edifecs (US), John Snow Labs (US), ITRex Group (US), KMS Healthcare (US), Appinventiv (India), Reveal HealthTech (US), Veritis (US), Optum (US), Health Catalyst (US), AMBOSS (Germany), Maruti Techlabs (India), DeepScribe (US), ForeSee Medical (US), Gnani.ai (India), Notable Health (US), Biofourmis (US), Suki AI (US), Wave Health Technologies (US), Corti (Denmark), CloudMex (US), Emtelligent (Canada), Enlitic (US), and Deep 6 AI (US).

Research Coverage

This research report categorizes the NLP in healthcare & life sciences market based on Offering (software and services), Deployment mode (cloud & on-premises), NLP type (natural language understanding (NLU) and natural language generation (NLG)), NLP technique (optical character recognition (OCR), named entity recognition (NER), sentiment analysis, text classification, topic modeling, text summarization, other NLP techniques), Application (patient care & engagement, clinical operations & decision support, biomedical research & drug development, administrative & operations management, genomics & precision medicine, medical education & knowledge dissemination and other applications), End User (enterprise (clinical practitioners, healthcare researchers, healthcare administrators, health insurance & payer professional, pharmaceutical & biotech companies and other end users), and Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America).

The scope of the report covers detailed information regarding the drivers, restraints, challenges, and opportunities influencing the growth of the NLP in healthcare & life sciences market. A detailed analysis of the key industry players was done to provide insights into their business overview, solutions, and services; key strategies; contracts, partnerships, agreements, new product & service launches, and mergers and acquisitions; and recent developments associated with the market. This report also covered the competitive analysis of upcoming startups in the market ecosystem.

Key Benefits of Buying the Report

The report will provide the market leaders/new entrants with information on the closest approximations of the revenue numbers for the overall NLP in healthcare & life sciences market and its subsegments. It will help stakeholders understand the competitive landscape and gain more insights to better position their business and plan suitable go-to-market strategies. It will also help stakeholders understand the market's pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

• Analysis of key drivers (NLP makes EHR data actionable by extracting insights from text and large datasets, enhanced decision-making by analyzing complex, unstructured clinical data and supports predictive analytics to identify trends and reduce risks).), restraints (Legacy IT systems hinder compatibility with modern NLP tools and high deployment costs and need for skilled personnel) ), opportunities (Real-time, personalized clinical decision support from diverse data, AI assistants streamlines patient engagement and documentation and multilingual translation improves global healthcare access)), and challenges (Integration with existing workflows requires major adjustments and lack of standardized frameworks for validating NLP effectiveness)).
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the NLP in healthcare & life sciences market.
• Market Development: Comprehensive information about lucrative markets - the report analyzes the NLP in healthcare & life sciences market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the NLP in healthcare & life sciences market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like Microsoft (US), Google (US), IBM (US), AWS (US), IQVIA (US), Oracle (US), Inovalon (US), Dolbey Systems (US), Averbis (Germany), SAS Institute (US), Solventum (US), Press Ganey (US), Ellipsis Health (US), Lexalytics (US), NVIDIA (US), GE Healthcare (US), Clinithink (US), HPE (US), Oncora Medical (US), Flatiron Health (US), Datavant (US), Edifecs (US), John Snow Labs (US), ITRex Group (US), KMS Healthcare (US), Appinventiv (India), Reveal HealthTech (US), Veritis (US), Optum (US), Health Catalyst (US), AMBOSS (Germany), Maruti Techlabs (India), DeepScribe (US), ForeSee Medical (US), Gnani.ai (India), Notable Health (US), Biofourmis (US), Suki AI (US), Wave Health Technologies (US), Corti (Denmark), CloudMex (US), Emtelligent (Canada), Enlitic (US), and Deep 6 AI (US). The report also helps stakeholders understand the pulse of the NLP in healthcare & life sciences market and provides them with information on key market drivers, restraints, challenges, and opportunities.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
• 1.3 MARKET SCOPE
  • 1.3.1 MARKET SEGMENTATION AND REGIONAL SCOPE
  • 1.3.2 INCLUSIONS AND EXCLUSIONS
  • 1.3.3 YEARS CONSIDERED
• 1.4 CURRENCY CONSIDERED
• 1.5 STAKEHOLDERS
• 1.6 SUMMARY OF CHANGES

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 2.1.1 SECONDARY DATA
    • 2.1.1.1 Key data from secondary sources
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 List of primary participants
    • 2.1.2.2 Breakdown of primaries
    • 2.1.2.3 Key data from primary sources
    • 2.1.2.4 Key industry insights
• 2.2 MARKET BREAKUP AND DATA TRIANGULATION
• 2.3 MARKET SIZE ESTIMATION
  • 2.3.1 TOP-DOWN APPROACH
  • 2.3.2 BOTTOM-UP APPROACH
• 2.4 MARKET FORECAST
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 RESEARCH LIMITATIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN NLP IN HEALTHCARE & LIFE SCIENCES MARKET
• 4.2 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY APPLICATION
• 4.3 NORTH AMERICA: NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY NLP TECHNIQUE AND END USER
• 4.4 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION

5 MARKET OVERVIEW

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Surging volume of unstructured clinical data
    • 5.2.1.2 Rising demand for enhanced care delivery and patient engagement
    • 5.2.1.3 Need for predictive analytics to improve significant health concerns
    • 5.2.1.4 Increasing focus on enhancing clinical decision support
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Clinical accuracy and reliability concerns
    • 5.2.2.2 Issues related to domain-specific language and medical terminology in NLP model development
    • 5.2.2.3 Complexity in integrating NLP with established healthcare system
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Rising adoption of computer-assisted coding to enhance productivity
    • 5.2.3.2 Emergence of advanced AI technology for generating valuable insights for healthcare
    • 5.2.3.3 Emergence of cognitive computing for medicine applications
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Model training data limitations
    • 5.2.4.2 High cost of implementation and maintenance of NLP technology
    • 5.2.4.3 Explainability and interpretability issues while deploying NLP algorithms
• 5.3 IMPACT OF 2025 US TARIFF-NLP IN HEALTHCARE & LIFE SCIENCES MARKET
  • 5.3.1 INTRODUCTION
  • 5.3.2 KEY TARIFF RATES
  • 5.3.3 PRICE IMPACT ANALYSIS
    • 5.3.3.1 Strategic shifts and emerging trends
  • 5.3.4 IMPACT ON COUNTRY/REGION
    • 5.3.4.1 US
      • 5.3.4.1.1 Strategic shifts and key observations
    • 5.3.4.2 China
      • 5.3.4.2.1 Strategic shifts and key observations
    • 5.3.4.3 Europe
      • 5.3.4.3.1 Strategic shifts and key observations
    • 5.3.4.4 India
      • 5.3.4.4.1 Strategic shifts and key observations
  • 5.3.5 IMPACT ON END-USE INDUSTRIES
    • 5.3.5.1 Clinical practitioners
    • 5.3.5.2 Healthcare Researchers
    • 5.3.5.3 Pharmaceutical & Biotech companies
• 5.4 EVOLUTION OF NLP IN HEALTHCARE & LIFE SCIENCES MARKET
• 5.5 NLP IN HEALTHCARE & LIFE SCIENCES MARKET: ARCHITECTURE
• 5.6 SUPPLY CHAIN ANALYSIS
• 5.7 ECOSYSTEM ANALYSIS
  • 5.7.1 SOFTWARE & SERVICE PROVIDERS BY APPLICATION
    • 5.7.1.1 Patient care & engagement
    • 5.7.1.2 Clinical operations & decision support
    • 5.7.1.3 Biomedical research & drug development
    • 5.7.1.4 Administrative & operations management
    • 5.7.1.5 Genomics & precision medicine
    • 5.7.1.6 Medical education & knowledge dissemination
• 5.8 INVESTMENT LANDSCAPE AND FUNDING SCENARIO
• 5.9 CASE STUDY ANALYSIS
  • 5.9.1 CASE STUDY 1: CSL BEHRING COLLABORATED WITH IQVIA'S NLP TEAM, LINGUAMATICS, TO CREATE PROOF OF CONCEPT
  • 5.9.2 CASE STUDY 2: ATRIUS HEALTH USED LINGUAMATICS I2E TO CREATE QUERIES TO EXTRACT CLINICAL DATA FROM FREE-TEXT FIELDS WITHIN CLINICIAN PROGRESS NOTES AND CLINICAL REPORTS
  • 5.9.3 CASE STUDY 3: HUMANA ADOPTED WATSON'S VOICE AGENT TO OFFER ENHANCED SELF-SERVICE CAPABILITIES TO HEALTHCARE PROVIDERS
  • 5.9.4 CASE STUDY 4: BIOPHARMACEUTICAL COMPANY DEPLOYED IQVIA'S SOLUTIONS TO CONDUCT HEALTH TECHNOLOGY ASSESSMENT
  • 5.9.5 CASE STUDY 5: PHILIPS ADOPTED AMAZON'S ELASTIC COMPUTE CLOUD (AMAZON EC2) TO ATTAIN SECURE, RESIZABLE COMPUTING CAPACITY
• 5.10 TECHNOLOGY ANALYSIS
  • 5.10.1 KEY TECHNOLOGIES
    • 5.10.1.1 Generative AI
    • 5.10.1.2 Natural Language Processing (NLP)
    • 5.10.1.3 Machine Learning
    • 5.10.1.4 Computer Vision
  • 5.10.2 COMPLIMENTARY TECHNOLOGIES
    • 5.10.2.1 Conversational AI
    • 5.10.2.2 Emotion AI
    • 5.10.2.3 Cloud computing
  • 5.10.3 ADJACENT TECHNOLOGIES
    • 5.10.3.1 Edge AI
    • 5.10.3.2 Blockchain
    • 5.10.3.3 AR/VR
• 5.11 REGULATORY LANDSCAPE
  • 5.11.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • 5.11.1.1 North America
      • 5.11.1.1.1 US
      • 5.11.1.1.2 Canada
    • 5.11.1.2 Europe
    • 5.11.1.3 Asia Pacific
      • 5.11.1.3.1 China
      • 5.11.1.3.2 India
      • 5.11.1.3.3 Japan
      • 5.11.1.3.4 South Korea
    • 5.11.1.4 Middle East & Africa
      • 5.11.1.4.1 UAE
      • 5.11.1.4.2 KSA
    • 5.11.1.5 Latin America
      • 5.11.1.5.1 Brazil
      • 5.11.1.5.2 Mexico
• 5.12 PATENT ANALYSIS
  • 5.12.1 METHODOLOGY
  • 5.12.2 PATENTS FILED, BY DOCUMENT TYPE
  • 5.12.3 INNOVATION AND PATENT APPLICATIONS
• 5.13 PRICING ANALYSIS
  • 5.13.1 AVERAGE SELLING PRICE OF KEY PLAYERS, BY OFFERING, 2025
  • 5.13.2 AVERAGE SELLING PRICE, BY APPLICATION, 2025
• 5.14 KEY CONFERENCES AND EVENTS, 2025-2026
• 5.15 NLP IN HEALTHCARE & LIFE SCIENCES MARKET: BUSINESS MODELS
  • 5.15.1 SAAS MODEL
  • 5.15.2 CONSULTING SERVICES MODEL
  • 5.15.3 REVENUE SHARING MODEL
  • 5.15.4 PAY-PER-USE MODEL
• 5.16 PORTER'S FIVE FORCES ANALYSIS
  • 5.16.1 THREAT OF NEW ENTRANTS
  • 5.16.2 THREAT OF SUBSTITUTES
  • 5.16.3 BARGAINING POWER OF SUPPLIERS
  • 5.16.4 BARGAINING POWER OF BUYERS
  • 5.16.5 INTENSITY OF COMPETITIVE RIVALRY
• 5.17 KEY STAKEHOLDERS AND BUYING CRITERIA
  • 5.17.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.17.2 BUYING CRITERIA
• 5.18 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS

6 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY OFFERING

• 6.1 INTRODUCTION
  • 6.1.1 OFFERING: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
• 6.2 SOFTWARE
  • 6.2.1 STANDALONE NLP SOFTWARE
    • 6.2.1.1 Deliver precise, customized, and secure NLP solutions
  • 6.2.2 INTEGRATED NLP SOFTWARE
    • 6.2.2.1 Enhance clinical workflows and insights
• 6.3 SERVICES
  • 6.3.1 PROFESSIONAL SERVICES
    • 6.3.1.1 Empower healthcare & life sciences with expert service solutions
    • 6.3.1.2 Training & Consulting Services
    • 6.3.1.3 System integration & implementation
    • 6.3.1.4 Support & maintenance
  • 6.3.2 MANAGED SERVICES
    • 6.3.2.1 Reliable NLP operations with comprehensive managed healthcare services

7 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY DEPLOYMENT MODE

• 7.1 INTRODUCTION
  • 7.1.1 DEPLOYMENT MODE: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
• 7.2 CLOUD
  • 7.2.1 LEVERAGE CLOUD-BASED NLP FOR SCALABLE AND COST-EFFECTIVE DATA PROCESSING SOLUTIONS
• 7.3 ON-PREMISES
  • 7.3.1 SECURE ON-PREMISES NLP DEPLOYMENT FOR COMPLIANCE AND DATA SOVEREIGNTY IN HEALTHCARE

8 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY NLP TYPE

• 8.1 INTRODUCTION
  • 8.1.1 NLP TYPE: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
• 8.2 NATURAL LANGUAGE UNDERSTANDING
  • 8.2.1 HARNESSING CLINICAL INSIGHTS BY UNDERSTANDING COMPLEX MEDICAL LANGUAGE IN HEALTHCARE
• 8.3 NATURAL LANGUAGE GENERATION
  • 8.3.1 DRIVING HEALTHCARE EFFICIENCY AND PATIENT ENGAGEMENT THROUGH ADVANCED SOLUTIONS

9 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY NLP TECHNIQUE

• 9.1 INTRODUCTION
  • 9.1.1 NLP TECHNIQUE: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
• 9.2 OPTICAL CHARACTER RECOGNITION
  • 9.2.1 FOCUS ON ENHANCING DATA PROCESSING INTO DIGITAL CONTENT TO DRIVE ADOPTION IN HEALTHCARE SERVICES
• 9.3 NAMED ENTITY RECOGNITION
  • 9.3.1 GROWING NEED TO ENHANCE DATA ORGANIZATION FOR IMPROVED PATIENT CARE TO PROPEL MARKET
• 9.4 SENTIMENT ANALYSIS
  • 9.4.1 NEED FOR IMPROVEMENT IN PATIENT CARE AND COMMUNICATION STRATEGIES TO DRIVE MARKET
• 9.5 TEXT CLASSIFICATION
  • 9.5.1 EMPHASIS ON EMPOWERING HEALTHCARE ORGANIZATIONS FOR ADVANCED ANALYSIS TO BOOST DEMAND
• 9.6 TOPIC MODELING
  • 9.6.1 NEED FOR UNCOVERING INSIGHTS AND TRENDS FROM TEXTUAL DATA TO DRIVE MARKET
• 9.7 TEXT SUMMARIZATION
  • 9.7.1 STREAMLINING MEDICAL INSIGHTS IN HEALTHCARE AND LIFE SCIENCES TO DRIVE MARKET
• 9.8 OTHER NLP TECHNIQUES

10 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY APPLICATION

• 10.1 INTRODUCTION
  • 10.1.1 APPLICATION: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
• 10.2 PATIENT CARE & ENGAGEMENT
  • 10.2.1 EMPOWERING PATIENT CARE AND ENGAGEMENT THROUGH ADVANCED NLP IN HEALTHCARE SYSTEMS
  • 10.2.2 CONVERSATIONAL AI & VIRTUAL ASSISTANTS
  • 10.2.3 REMOTE MONITORING & TELEHEALTH SUPPORT
  • 10.2.4 PATIENT FEEDBACK & SENTIMENT ANALYSIS
  • 10.2.5 HEALTH RISK ASSESSMENT
  • 10.2.6 OTHERS
• 10.3 CLINICAL OPERATIONS & DECISION SUPPORT
  • 10.3.1 UNLOCKING CLINICAL INSIGHTS AND STREAMLINING OPERATIONS WITH NLP FOR ENHANCED DECISION-MAKING AND EFFICIENCY
  • 10.3.2 CLINICAL DOCUMENTATION & TRANSCRIPTION
  • 10.3.3 MEDICAL CODING & BILLING AUTOMATION
  • 10.3.4 CLINICAL DECISION SUPPORT
  • 10.3.5 CLINICAL TRIAL MATCHING
  • 10.3.6 OTHERS
• 10.4 BIOMEDICAL RESEARCH & DRUG DEVELOPMENT
  • 10.4.1 ACCELERATING DRUG DISCOVERY AND RESEARCH INSIGHTS USING NLP IN HEALTHCARE
  • 10.4.2 LITERATURE MINING & KNOWLEDGE EXTRACTION
  • 10.4.3 DRUG DISCOVERY & REPURPOSING
  • 10.4.4 CLINICAL TRIAL DESIGN & OPTIMIZATION
  • 10.4.5 PHARMACOVIGILANCE & SAFETY MONITORING
  • 10.4.6 OTHERS
• 10.5 ADMINISTRATIVE & OPERATIONS MANAGEMENT
  • 10.5.1 STREAMLINING ADMINISTRATIVE WORKFLOWS WITH NLP TO BOOST EFFICIENCY AND ACCURACY IN HEALTHCARE OPERATIONS
  • 10.5.2 PRIOR AUTHORIZATION & UTILIZATION MANAGEMENT
  • 10.5.3 PROVIDER PERFORMANCE & QUALITY REPORTING
  • 10.5.4 INTEROPERABILITY & DATA NORMALIZATION
  • 10.5.5 REVENUE CYCLE MANAGEMENT
  • 10.5.6 OTHERS
• 10.6 GENOMICS & PRECISION MEDICINE
  • 10.6.1 UNLOCKING GENOMIC INSIGHTS WITH NLP TO ENHANCE PRECISION MEDICINE AND PERSONALIZED CARE
  • 10.6.2 GENOMIC REPORT INTERPRETATION
  • 10.6.3 INTEGRATING GENOMIC & CLINICAL DATA
  • 10.6.4 OTHERS
• 10.7 MEDICAL EDUCATION & KNOWLEDGE DISSEMINATION
  • 10.7.1 ENHANCING MEDICAL EDUCATION AND KNOWLEDGE SHARING WITH NLP FOR PERSONALIZED, EFFICIENT HEALTHCARE LEARNING
• 10.8 OTHER APPLICATIONS

11 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY END USER

• 11.1 INTRODUCTION
  • 11.1.1 END USER: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
• 11.2 CLINICAL PRACTITIONERS
  • 11.2.1 GROWING NEED TO ENHANCE TREATMENT PLANNING TO SPUR DEMAND
  • 11.2.2 PHYSICIANS/DOCTORS
  • 11.2.3 NURSES
  • 11.2.4 PHARMACISTS
  • 11.2.5 OTHERS
• 11.3 HEALTHCARE RESEARCHERS
  • 11.3.1 NEED FOR ANALYZING LARGE AMOUNT OF MEDICAL DATA FROM VARIOUS SOURCES TO DRIVE MARKET
  • 11.3.2 CLINICAL RESEARCHERS
  • 11.3.3 BIOMEDICAL SCIENTISTS
  • 11.3.4 EPIDEMIOLOGISTS
  • 11.3.5 OTHERS
• 11.4 HEALTHCARE ADMINISTRATORS
  • 11.4.1 FOCUS ON ENHANCING OPERATIONAL EFFICIENCY AND DECISION-MAKING TO ENCOURAGE MARKET EXPANSION
  • 11.4.2 HOSPITAL ADMINISTRATORS
  • 11.4.3 HEALTH IT MANAGERS
  • 11.4.4 HEALTHCARE DATA ANALYST
  • 11.4.5 OTHERS
• 11.5 HEALTH INSURANCE & PAYER PROFESSIONALS
  • 11.5.1 USE OF NLP TECHNIQUES TO IMPROVE VARIOUS ASPECTS OF OPERATIONS
  • 11.5.2 HEALTH INSURANCE COMPANIES
  • 11.5.3 GOVERNMENT HEALTH AGENCIES
  • 11.5.4 OTHERS
• 11.6 PHARMACEUTICAL & BIOTECH COMPANIES
  • 11.6.1 EMPHASIS ON GAINING INSIGHTS INTO DRUG SAFETY TO DRIVE ADOPTION OF NLP TECHNIQUES
  • 11.6.2 MEDICAL AFFAIRS & MARKET RESEARCHERS
  • 11.6.3 REGULATORY AFFAIRS
  • 11.6.4 PHARMACOVIGILANCE DEPARTMENT
  • 11.6.5 OTHERS
• 11.7 OTHER END USERS

12 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION

• 12.1 INTRODUCTION
• 12.2 NORTH AMERICA
  • 12.2.1 NORTH AMERICA: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
  • 12.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 12.2.3 US
    • 12.2.3.1 Driving innovation and efficiency in healthcare and life sciences with NLP
  • 12.2.4 CANADA
    • 12.2.4.1 Accelerating healthcare innovation and research through NLP technology integration
• 12.3 EUROPE
  • 12.3.1 EUROPE: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
  • 12.3.2 EUROPE: MACROECONOMIC OUTLOOK
  • 12.3.3 UK
    • 12.3.3.1 Advancing national NLP integration in NHS for real-time clinical insights and patient engagement
  • 12.3.4 GERMANY
    • 12.3.4.1 Driving AI-based diagnostics and ensuring GDPR-compliant NLP solutions in healthcare systems
  • 12.3.5 FRANCE
    • 12.3.5.1 Accelerating healthcare innovation with government-backed NLP initiatives and multilingual medical applications
  • 12.3.6 ITALY
    • 12.3.6.1 Transforming clinical data management and enhancing predictive analytics through NLP adoption
  • 12.3.7 SPAIN
    • 12.3.7.1 Digitally empowering public healthcare and extracting actionable insights from clinical text with NLP
  • 12.3.8 REST OF EUROPE
• 12.4 ASIA PACIFIC
  • 12.4.1 ASIA PACIFIC: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
  • 12.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 12.4.3 CHINA
    • 12.4.3.1 Advancing NLP-driven clinical efficiency and patient care through AI innovation in China
  • 12.4.4 JAPAN
    • 12.4.4.1 Driving efficient healthcare and personalized care for aging population using advanced NLP technologies
  • 12.4.5 INDIA
    • 12.4.5.1 Driving NLP adoption by digitizing records, enhancing telehealth, and improving patient engagement in India
  • 12.4.6 SOUTH KOREA
    • 12.4.6.1 Advancing accurate clinical data analysis and AI diagnostics to transform healthcare
  • 12.4.7 AUSTRALIA & NEW ZEALAND
    • 12.4.7.1 Enhancing clinical data management and personalized care through advanced NLP adoption
  • 12.4.8 ASEAN
    • 12.4.8.1 Driving multilingual NLP solutions and digital healthcare transformation to enhance ASEAN patient care access
  • 12.4.9 REST OF ASIA PACIFIC
• 12.5 MIDDLE EAST & AFRICA
  • 12.5.1 MIDDLE EAST & AFRICA: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
  • 12.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 12.5.3 SAUDI ARABIA
    • 12.5.3.1 Streamlining clinical documentation for better patient care outcomes to drive market
  • 12.5.4 UAE
    • 12.5.4.1 Government Leadership and Collaborative Innovation to boost NLP adoption in healthcare
  • 12.5.5 SOUTH AFRICA
    • 12.5.5.1 Multilingual demands and digital gaps to drive demand for NLP
  • 12.5.6 ISRAEL
    • 12.5.6.1 Startup Innovation and institutional support drive NLP demand in healthcare and life sciences
  • 12.5.7 REST OF MIDDLE EAST & AFRICA
• 12.6 LATIN AMERICA
  • 12.6.1 LATIN AMERICA: NLP IN HEALTHCARE & LIFE SCIENCES MARKET DRIVERS
  • 12.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 12.6.3 BRAZIL
    • 12.6.3.1 Advanced NLP adoption with new regulations and partnerships to drive market
  • 12.6.4 MEXICO
    • 12.6.4.1 Enhancing clinical decision support to boost NLP adoption in healthcare sector
  • 12.6.5 ARGENTINA
    • 12.6.5.1 Need or deployment of sophisticated algorithms to analyze clinical notes to boost demand
  • 12.6.6 REST OF LATIN AMERICA

13 COMPETITIVE LANDSCAPE

• 13.1 OVERVIEW
• 13.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2022-2025
• 13.3 REVENUE ANALYSIS, 2020-2024
• 13.4 MARKET SHARE ANALYSIS, 2024
• 13.5 PRODUCT COMPARATIVE ANALYSIS
  • 13.5.1 PRODUCT COMPARATIVE ANALYSIS, BY OFFERING
    • 13.5.1.1 Health Discovery (Averbis)
    • 13.5.1.2 Fusion CDI (Dolbey Systems)
    • 13.5.1.3 Clinical Documentation Integrity (Solventum)
    • 13.5.1.4 Cloud Healthcare API (Google)
    • 13.5.1.5 Inovalon ONE platform (Inovalon)
  • 13.5.2 PRODUCT COMPARATIVE ANALYSIS, BY APPLICATION
    • 13.5.2.1 IBM Watsonx Assistant (IBM)
    • 13.5.2.2 Microsoft Dragon CoPilot (Microsoft)
    • 13.5.2.3 Oracle Clinical Digital Assistant (Oracle)
    • 13.5.2.4 IQVIA NLP Risk Adjustment (IQVIA)
    • 13.5.2.5 AWS HealthLake (AWS)
• 13.6 COMPANY VALUATION AND FINANCIAL METRICS
• 13.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
  • 13.7.1 STARS
  • 13.7.2 EMERGING LEADERS
  • 13.7.3 PERVASIVE PLAYERS
  • 13.7.4 PARTICIPANTS
  • 13.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
    • 13.7.5.1 Company footprint
    • 13.7.5.2 Regional footprint
    • 13.7.5.3 Offering footprint
    • 13.7.5.4 Application footprint
    • 13.7.5.5 End user footprint
• 13.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
  • 13.8.1 PROGRESSIVE COMPANIES
  • 13.8.2 RESPONSIVE COMPANIES
  • 13.8.3 DYNAMIC COMPANIES
  • 13.8.4 STARTING BLOCKS
  • 13.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
    • 13.8.5.1 Detailed list of key startups/SMEs
    • 13.8.5.2 Competitive benchmarking of key startups/SMEs
• 13.9 COMPETITIVE SCENARIO AND TRENDS
  • 13.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS
  • 13.9.2 DEALS

14 COMPANY PROFILES

• 14.1 INTRODUCTION
• 14.2 KEY PLAYERS
  • 14.2.1 IBM
    • 14.2.1.1 Business overview
    • 14.2.1.2 Products/Solutions/Services offered
    • 14.2.1.3 Recent developments
    • 14.2.1.4 MnM view
      • 14.2.1.4.1 Right to win
      • 14.2.1.4.2 Strategic choices
      • 14.2.1.4.3 Weaknesses and competitive threats
  • 14.2.2 MICROSOFT
    • 14.2.2.1 Business overview
    • 14.2.2.2 Products/Solutions/Services offered
    • 14.2.2.3 Recent developments
    • 14.2.2.4 MnM view
      • 14.2.2.4.1 Right to win
      • 14.2.2.4.2 Strategic choices
      • 14.2.2.4.3 Weaknesses and competitive threats
  • 14.2.3 GOOGLE
    • 14.2.3.1 Business overview
    • 14.2.3.2 Products/Solutions/Services offered
    • 14.2.3.3 Recent developments
    • 14.2.3.4 MnM view
      • 14.2.3.4.1 Right to win
      • 14.2.3.4.2 Strategic choices
      • 14.2.3.4.3 Weaknesses and competitive threats
  • 14.2.4 AWS
    • 14.2.4.1 Business overview
    • 14.2.4.2 Products/Solutions/Services offered
    • 14.2.4.3 Recent developments
    • 14.2.4.4 MnM view
      • 14.2.4.4.1 Right to win
      • 14.2.4.4.2 Strategic choices
      • 14.2.4.4.3 Weaknesses and competitive threats
  • 14.2.5 IQVIA
    • 14.2.5.1 Business overview
    • 14.2.5.2 Products/Solutions/Services offered
    • 14.2.5.3 Recent developments
    • 14.2.5.4 MnM view
      • 14.2.5.4.1 Right to win
      • 14.2.5.4.2 Strategic choices
      • 14.2.5.4.3 Weaknesses and competitive threats
  • 14.2.6 ORACLE
    • 14.2.6.1 Business overview
    • 14.2.6.2 Products/Solutions/Services offered
    • 14.2.6.3 Recent developments
  • 14.2.7 INOVALON
    • 14.2.7.1 Business overview
    • 14.2.7.2 Products/Solutions/Services offered
    • 14.2.7.3 Recent developments
  • 14.2.8 DOLBEY SYSTEMS
    • 14.2.8.1 Business overview
    • 14.2.8.2 Products/Solutions/Services offered
    • 14.2.8.3 Recent developments
  • 14.2.9 AVERBIS
    • 14.2.9.1 Business overview
    • 14.2.9.2 Products/Solutions/Services offered
    • 14.2.9.3 Recent developments
  • 14.2.10 SAS INSTITUTE
    • 14.2.10.1 Business overview
    • 14.2.10.2 Products/Solutions/Services offered
    • 14.2.10.3 Recent developments
  • 14.2.11 SOLVENTUM
    • 14.2.11.1 Business overview
    • 14.2.11.2 Products/Solutions/Services offered
    • 14.2.11.3 Recent developments
  • 14.2.12 PRESS GANEY
  • 14.2.13 ELLIPSIS HEALTH
  • 14.2.14 LEXALYTICS
  • 14.2.15 NVIDIA
  • 14.2.16 GE HEALTHCARE
  • 14.2.17 CLINITHINK
  • 14.2.18 HPE
  • 14.2.19 ONCORA MEDICAL
  • 14.2.20 FLATIRON HEALTH
  • 14.2.21 DATAVANT
  • 14.2.22 EDIFECS
  • 14.2.23 JOHN SNOW LABS
  • 14.2.24 ITREX GROUP
  • 14.2.25 KMS HEALTHCARE
  • 14.2.26 APPINVENTIV
  • 14.2.27 REVEAL HEALTHTECH
  • 14.2.28 VERITIS
  • 14.2.29 OPTUM
  • 14.2.30 HEALTH CATALYST
  • 14.2.31 AMBOSS
  • 14.2.32 MARUTI TECHLABS
  • 14.2.33 DEEPSCRIBE
• 14.3 OTHER PLAYERS
  • 14.3.1 FORESEE MEDICAL
  • 14.3.2 GNANI.AI
  • 14.3.3 NOTABLE HEALTH
  • 14.3.4 BIOFOURMIS
  • 14.3.5 SUKI AI
  • 14.3.6 WAVE HEALTH TECHNOLOGIES
  • 14.3.7 CORTI
  • 14.3.8 CLOUDMEDX
  • 14.3.9 EMTELLIGENT
  • 14.3.10 ENLITIC
  • 14.3.11 DEEP 6 AI

15 ADJACENT AND RELATED MARKETS

• 15.1 INTRODUCTION
• 15.2 ARTIFICIAL INTELLIGENCE (AI) MARKET - GLOBAL FORECAST TO 2030
  • 15.2.1 MARKET DEFINITION
  • 15.2.2 MARKET OVERVIEW
    • 15.2.2.1 Artificial intelligence market, by offering
    • 15.2.2.2 Artificial intelligence market, by technology
    • 15.2.2.3 Artificial intelligence market, by business function
    • 15.2.2.4 Artificial intelligence market, by vertical
    • 15.2.2.5 Artificial intelligence market, by region
• 15.3 NATURAL LANGUAGE UNDERSTANDING MARKET - GLOBAL FORECAST TO 2029
  • 15.3.1 MARKET DEFINITION
  • 15.3.2 MARKET OVERVIEW
    • 15.3.2.1 Natural Language Understanding market, by offering
    • 15.3.2.2 Natural Language Understanding market, by type
    • 15.3.2.3 Natural Language Understanding market, by application
    • 15.3.2.4 Natural Language Understanding Market, by Vertical
    • 15.3.2.5 Natural Language Understanding Market, by region

16 APPENDIX

• 16.1 DISCUSSION GUIDE
• 16.2 KNOWLEDGE STORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 16.3 AVAILABLE CUSTOMIZATIONS
• 16.4 RELATED REPORTS
• 16.5 AUTHOR DETAILS