This report was recently updated on November 19 2024 with the latest and most recent
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Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market Size, Trends & Analysis - Forecasts to 2026 By Component (Standalone Solutions and Services [Support & Maintenance and Professional Services]), By Type (Rule-Based Natural Language Processing, Statistical Natural Language Processing, and Hybrid Natural Language Processing), By Application (Interactive Voice Response (IVR), Pattern & Image Recognition, Auto Coding, Classification & Categorization, Text & Speech Analytics, and Others (Information Extraction and Report Generation), By Deployment Mode (Cloud and On-premises), By Organization Size (Large Enterprise and Small and Medium-sized Enterprises (SMEs)), By End-Users ( NLP for Physicians, NLP for Researchers, NLP for Patients, and NLP for Clinical Operators), By Region (North America, Asia Pacific, Europe, Latin America, Middle East & Africa); End-User Landscape, Company Market Share Analysis, and Competitor Analysis
Natural language processing (NLP) is a breakthrough that assists machines in comprehending both textual and verbal human language by evaluating human-computer communication. NLP techniques extract data from enormous amounts of clinical information and increase its viability for better preparation and assessment.
Customers' requests for an electronic health record competent in recording, analyzing, and differentiating relevant narrative information as well as ambiguous data captured via natural language processing apps are increasing significantly. Furthermore, the healthcare and life sciences industries are seeing significant technical progress as a result of growing customer expectations for improved healthcare services. Furthermore, patients are becoming more conscious of their health and using predictive analytics to decrease health-related hazards as well as enhance medical conditions. Moreover, natural language processing applications connect healthcare professionals with social media data on patients via webpages, Google search, and social networking sites, allowing healthcare professionals to enhance customer engagement and change based on consumer inclinations. Every one of these aspects has aided the advancement of natural language processing in the healthcare and life sciences markets. Nevertheless, the business is hampered by special medical sub-languages and low input information integrity.
The employment of predictive analytics to minimize risk and alleviate critical health issues is growing, as is the application of EHR data for improved patient care and the capacity to interpret context from unrelated streams of data. These are the causes driving the expansion of the natural language processing (NLP) market in healthcare and life sciences. The constraints limiting natural language processing (NLP) in the healthcare and life sciences business include inadequate data integrity of sources and particular sub-medical languages. As a possibility, an NLP system is trained to grasp the content of patients' medical information. One of the obstacles confronted by the natural language processing (NLP) sector in healthcare and life sciences is concerns about data confidentiality and transparency, which are accountable for halting researchers' development.
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With respect to components, the market can be classified as standalone solutions, and services. Services include support & maintenance and professional services. While addressing components, it is worth noting that the service segment is presumed to predominate the market. The rising need for enlightened healthcare solutions and access to information linked with provided treatment solutions drives up demand for specialist services to efficiently handle clinical data and enable better service capabilities to care customers. The growing demand for expert solutions correlates to the service segment's market share.
Based on types of NLP, the market can be categorized as rule-based natural language processing, statistical natural language processing, and hybrid natural language processing. The rule-based NLP segment is presumed to hold the largest market share in terms of type. This sort of NLP focuses on pattern-matching, a skill that is extremely useful in the healthcare industry. The aforementioned attribute is advantageous for the healthcare industry since it aids in improving the EHR process by aiding in the discovery of arbitrary terms and increasing the efficiency of data management. It leads to greater demand for this sort of NLP, which adds to the Rule-Based NLP segment's market share. The Hybrid NLP segment is expected to rise at the fastest rate. The Hybrid NLP segment's development rate is due to its efficacy in responding to complicated sentence patterns, which is leading to its rising recognition.
As per the applications, the market can be categorized as namely, interactive voice response (IVR), pattern & image recognition, auto coding, classification & categorization, text & speech analytics, and others. Others include information extraction and report generation. The pattern and image recognition segment is expected to dominate the market amongst applications. The application of Artificial Intelligence (AI) is projected to expand the horizons of healthcare by improving diagnostic and therapeutic tools and assisting healthcare practitioners in illness prognosis. Computer vision and Machine Learning (ML) algorithms have also contributed to the diagnosis of pre-cancerous tumors utilizing the finest features in tissue imaging, enhancing the specificity and precision of cancer diagnostic tests in the detection of skin cancer. For example, AI scientists have built computer vision algorithms that can interpret photos and biopsy samples of a cancer patient and how their skin changes considerably speedier and more precisely than a professional.
As per the mode of deployment, the market can be categorized as cloud and on-premise. The cloud deployment model is likely to predominate in the market. The significant volume of vendors in the market provides cloud-based NLP solutions to substantially optimize revenues and the device management procedure. The employment of cloud-based NLP in healthcare and life sciences systems is predicted to increase due to attributes such as convenient information management, cost-effectiveness, agility, adaptability, flexibility, and effective management. Cloud-based NLP solutions are preferred by businesses because they assist their provincial, cross-regional, or cross-country information restoration strategies. This helps enterprises to guarantee catastrophe resiliency.
With respect to the organization size, the market can be categorized as, small and medium-sized enterprises (SMEs) and large enterprises. Throughout the forecast period, the large enterprise segment will have a larger market share. Major organizations have recourse to a vast volume of information created from diverse sources. There is a requirement for legitimate information insights. The SME segment, on the other hand, is predicted to increase at a faster CAGR throughout the forecast period. SMEs are rapidly expanding and eager to adopt NLP on the cloud, which will allow them to analyze massive amounts of data and create faster choices in order to provide the best possible patient care.
As per the end-user, the market can be categorized as NLP for physicians, researchers, patients, and clinical operators. Researchers’ segment is presumed to dominate the market. Because of the nature and volume of data created by healthcare organizations, the NLP for researcher’s area is the most impacted by Artificial Intelligence (AI) trends and potential. For qualitative research, scientists frequently turn to NLP technologies. Thus, the advancement of NLP-enabled qualitative approaches may offer clinical researchers novel resources for investigating study problems that might not have been investigated otherwise. Medical scientists are employing natural language processing (NLP) and machine learning (ML) to enhance care collaboration by evaluating massive amounts of unorganized health information and extracting useful insights.
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This market by region can be classified into North America (the US, Canada, and Mexico), Asia Pacific (India, China, Japan, Malaysia, Singapore, and the Rest of Asia Pacific), Europe (Germany, United Kingdom, Italy, France, Spain, Netherlands, and Rest of Europe), Middle East & Africa and Central & South America. North America contributes the largest income to this market. The region is seeing tremendous advancements in the NLP industry in healthcare and life sciences. In North America, NLP technologies are growing in popularity in patterns and picture recognition. These technologies provide more versatile, adaptable, and cost-effective storage options, as well as enhanced analytics capabilities. Numerous North American NLP solution vendors are exploring the marketplace by merging AI technologies including machine learning and natural language processing with their pre-existing EHRs. Developing technological improvements in these sectors, as well as increased use of patient medical records solutions, is driving the evolution of the NLP market in healthcare and life sciences. The Asia Pacific region is expected to grow at the highest rate, as most healthcare businesses seek the benefits of NLP approaches, which will help them provide tailored client experiences and increase processing efficiency. This is due to the region's healthcare practitioners' increased use of AI tools. APAC's rapid expansion in healthcare information is expected to drive demand for NLP technology, as it becomes increasingly important to uncover new insights to enhance patient medical results.
3M, Apple, Google, Microsoft, A3logics, AlchemyAPI, Apixio, Aylien, Dolbey Systems, Fluxifi, HP, IBM, Linguamatics, Mmodal, Netbase, Nuance Communication, SAS Institute, Textalytics, and Verint Systems, amongst others, are the key players in the market.
Please note: This is not an exhaustive list of companies profiled in the report.
Chapter 1 Methodology
1.1 Market Scope & Definitions
1.2 Estimates & Forecast Calculation
1.3 Historical Data Overview And Validation
1.4 Data Sources
1.4.1 Secondary
1.4.2 Primary
Chapter 2 Report Outlook
2.1 Natural Language Processing (NLP) in Healthcare and Life Sciences Industry Overview, 2016-2026
2.1.1 Industry Overview
2.1.2 Component Overview
2.1.3 Type Overview
2.1.4 Application Overview
2.1.5 Deployment Mode Overview
2.1.6 Organization Size Overview
2.1.7 End-Users Overview
2.1.4 Regional Overview
Chapter 3 Natural Language Processing (NLP) in Healthcare and Life Sciences Market Trends
3.1 Market Segmentation
3.2 Industry Background, 2016-2026
3.3 Market Key Trends
3.3.1 Positive Trends
3.3.1.1 Technology Advancement in Healthcare Industry
3.3.1.2 Increasing Expenditure on Healthcare AI
3.3.2 Industry Challenges
3.3.2.1 Limited Study and Industry Participants
3.4 Prospective Growth Scenario
3.4.1 Component Growth Scenario
3.4.2 Type Growth Scenario
3.4.3 Application Growth Scenario
3.4.4 Deployment Mode Growth Scenario
3.4.5 Organization Size Growth Scenario
3.4.6 End-Users Growth Scenario
3.5 COVID-19 Influence over Industry Growth
3.6 Porter’s Analysis
3.7 PESTEL Analysis
3.8 Value Chain & Supply Chain Analysis
3.9 Regulatory Framework
3.9.1 North America
3.9.2 Europe
3.9.3 APAC
3.9.4 LATAM
3.9.5 MEA
3.10 Technology Overview
3.11 Market Share Analysis, 2020
3.11.1 Company Positioning Overview, 2020
Chapter 4 Natural Language Processing (NLP) in Healthcare and Life Sciences Market, By Component
4.1 Component Outlook
4.2 Standalone Solutions
4.2.1 Market Size, By Region, 2016-2026 (USD Million)
4.3 Services
4.3.1 Market Size, By Region, 2016-2026 (USD Million)
4.3.2 Support & Maintenance
4.3.2.1 Market Size, By Region, 2016-2026 (USD Million)
4.3.3 Professional Services
4.3.3.1 Market Size, By Region, 2016-2026 (USD Million)
Chapter 5 Natural Language Processing (NLP) in Healthcare and Life Sciences Market, By Type
5.1 Type Outlook
5.2 Rule-Based Natural Language Processing
5.2.1 Market Size, By Region, 2016-2026 (USD Million)
5.3 Statistical Natural Language Processing
5.3.1 Market Size, By Region, 2016-2026 (USD Million)
5.4 Hybrid Natural Language Processing
5.4.1 Market Size, By Region, 2016-2026 (USD Million)
Chapter 6 Natural Language Processing (NLP) in Healthcare and Life Sciences Market, By Application
6.1 Application Outlook
6.2 Interactive Voice Response (IVR)
6.2.1 Market Size, By Region, 2016-2026 (USD Million)
6.3 Pattern & Image Recognition
6.3.1 Market Size, By Region, 2016-2026 (USD Million)
6.4 Auto Coding
6.4.1 Market Size, By Region, 2016-2026 (USD Million)
6.5 Classification & Categorization
6.5.1 Market Size, By Region, 2016-2026 (USD Million)
6.6 Text & Speech Analytics
6.6.1 Market Size, By Region, 2016-2026 (USD Million)
6.7 Others
6.7.1 Market Size, By Region, 2016-2026 (USD Million)
6.7.2 Information Extraction
6.7.2.1 Market Size, By Region, 2016-2026 (USD Million)
6.7.3 Report Generation
6.7.3.1 Market Size, By Region, 2016-2026 (USD Million)
Chapter 7 Natural Language Processing (NLP) in Healthcare and Life Sciences Market, By Deployment Mode
7.1 Deployment Mode Outlook
7.2 Cloud
7.2.1 Market Size, By Region, 2016-2026 (USD Million)
7.3 On-premises
7.3.1 Market Size, By Region, 2016-2026 (USD Million)
Chapter 8 Natural Language Processing (NLP) in Healthcare and Life Sciences Market, By Organization Size
8.1 Organization Size Outlook
8.2 Large Enterprise
8.2.1 Market Size, By Region, 2016-2026 (USD Million)
8.3 Small and Medium-sized Enterprises (SMEs)
8.3.1 Market Size, By Region, 2016-2026 (USD Million)
Chapter 9 Natural Language Processing (NLP) in Healthcare and Life Sciences Market, By End-Users
9.1 Organization Size Outlook
9.2 NLP for Physicians
9.2.1 Market Size, By Region, 2016-2026 (USD Million)
9.3 NLP for Researchers
9.3.1 Market Size, By Region, 2016-2026 (USD Million)
9.4 NLP for Patients
9.4.1 Market Size, By Region, 2016-2026 (USD Million)
9.5 NLP for Clinical Operators
9.5.1 Market Size, By Region, 2016-2026 (USD Million)
Chapter 10 Natural Language Processing (NLP) in Healthcare and Life Sciences Market, By Region
10.1 Regional outlook
10.2 North America
10.2.1 Market Size, By Country 2016-2026 (USD Million)
10.2.2 Market Size, By Component, 2016-2026 (USD Million)
10.2.3 Market Size, By Type, 2016-2026 (USD Million)
10.2.4 Market Size, By Application, 2016-2026 (USD Million)
10.2.5 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.2.6 Market Size, By Organization Size, 2016-2026 (USD Million)
10.2.7 Market Size, By End-Users, 2016-2026 (USD Million)
10.2.8 U.S.
10.2.8.1 Market Size, By Component, 2016-2026 (USD Million)
10.2.8.2 Market Size, By Type, 2016-2026 (USD Million)
10.2.8.3 Market Size, By Application, 2016-2026 (USD Million)
10.2.8.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.2.8.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.2.8.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.2.9 Canada
10.2.9.1 Market Size, By Component, 2016-2026 (USD Million)
10.2.9.2 Market Size, By Type, 2016-2026 (USD Million)
10.2.9.3 Market Size, By Application, 2016-2026 (USD Million)
10.2.9.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.2.9.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.2.9.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.3 Europe
10.3.1 Market Size, By Country 2016-2026 (USD Million)
10.3.2 Market Size, By Component, 2016-2026 (USD Million)
10.3.3 Market Size, By Type, 2016-2026 (USD Million)
10.3.4 Market Size, By Application, 2016-2026 (USD Million)
10.3.5 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.3.6 Market Size, By Organization Size, 2016-2026 (USD Million)
10.3.7 Market Size, By End-Users, 2016-2026 (USD Million)
10.3.8 Germany
10.3.8.1 Market Size, By Component, 2016-2026 (USD Million)
10.3.8.2 Market Size, By Type, 2016-2026 (USD Million)
10.3.8.3 Market Size, By Application, 2016-2026 (USD Million)
10.3.8.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.3.8.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.3.8.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.3.9 UK
10.3.9.1 Market Size, By Component, 2016-2026 (USD Million)
10.3.9.2 Market Size, By Application, 2016-2026 (USD Million)
10.3.9.3 Market Size, By Type, 2016-2026 (USD Million)
10.3.9.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.3.9.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.3.9.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.3.10 France
10.3.10.1 Market Size, By Component, 2016-2026 (USD Million)
10.3.10.2 Market Size, By Type, 2016-2026 (USD Million)
10.3.10.3 Market Size, By Application, 2016-2026 (USD Million)
10.3.10.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.3.10.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.3.10.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.3.11 Italy
10.3.11.1 Market Size, By Component, 2016-2026 (USD Million)
10.3.11.2 Market Size, By Type, 2016-2026 (USD Million)
10.3.11.3 Market Size, By Application, 2016-2026 (USD Million)
10.3.11.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.3.11.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.3.11.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.3.12 Spain
10.3.12.1 Market Size, By Component, 2016-2026 (USD Million)
10.3.12.2 Market Size, By Type, 2016-2026 (USD Million)
10.3.12.3 Market Size, By Application, 2016-2026 (USD Million)
10.3.12.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.3.12.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.3.12.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.3.13 Russia
10.3.13.1 Market Size, By Component, 2016-2026 (USD Million)
10.3.13.2 Market Size, By Type, 2016-2026 (USD Million)
10.3.13.3 Market Size, By Application, 2016-2026 (USD Million)
10.3.13.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.3.13.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.3.13.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.4 Asia Pacific
10.4.1 Market Size, By Country 2016-2026 (USD Million)
10.4.2 Market Size, By Component, 2016-2026 (USD Million)
10.4.3 Market Size, By Type, 2016-2026 (USD Million)
10.4.4 Market Size, By Application, 2016-2026 (USD Million)
10.4.5 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.4.6 Market Size, By Organization Size, 2016-2026 (USD Million)
10.4.7 Market Size, By End-Users, 2016-2026 (USD Million)
10.4.8 China
10.4.8.1 Market Size, By Component, 2016-2026 (USD Million)
10.4.8.2 Market Size, By Type, 2016-2026 (USD Million)
10.4.8.3 Market Size, By Application, 2016-2026 (USD Million)
10.4.8.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.4.8.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.4.8.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.4.9 India
10.4.9.1 Market Size, By Component, 2016-2026 (USD Million)
10.4.9.2 Market Size, By Type, 2016-2026 (USD Million)
10.4.9.3 Market Size, By Application, 2016-2026 (USD Million)
10.4.9.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.4.9.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.4.9.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.4.10 Japan
10.4.10.1 Market Size, By Component, 2016-2026 (USD Million)
10.4.10.2 Market Size, By Type, 2016-2026 (USD Million)
10.4.10.3 Market Size, By Application, 2016-2026 (USD Million)
10.4.10.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.4.10.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.4.10.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.4.11 Australia
10.4.11.1 Market Size, By Component, 2016-2026 (USD Million)
10.4.11.2 Market size, By Type, 2016-2026 (USD Million)
10.4.11.3 Market size, By Application, 2016-2026 (USD Million)
10.4.11.4 Market size, By Deployment Mode, 2016-2026 (USD Million)
10.4.11.5 Market size, By Organization Size, 2016-2026 (USD Million)
10.4.11.6 Market size, By End-Users, 2016-2026 (USD Million)
10.4.12 South Korea
10.4.12.1 Market Size, By Component, 2016-2026 (USD Million)
10.4.12.2 Market Size, By Type, 2016-2026 (USD Million)
10.4.12.3 Market Size, By Application, 2016-2026 (USD Million)
10.4.12.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.4.12.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.4.12.6 Market Size, By End-Users, 2016-2026 (USD Million)
6.5 Latin America
10.5.1 Market Size, By Country 2016-2026 (USD Million)
10.5.2 Market Size, By Component, 2016-2026 (USD Million)
10.5.3 Market Size, By Type, 2016-2026 (USD Million)
10.5.4 Market Size, By Application, 2016-2026 (USD Million)
10.5.5 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.5.6 Market Size, By Organization Size, 2016-2026 (USD Million)
10.5.7 Market Size, By End-Users, 2016-2026 (USD Million)
10.5.8 Brazil
10.5.8.1 Market Size, By Component, 2016-2026 (USD Million)
10.5.8.2 Market Size, By Type, 2016-2026 (USD Million)
10.5.8.3 Market Size, By Application, 2016-2026 (USD Million)
10.5.8.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.5.8.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.5.8.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.5.9 Mexico
10.5.9.1 Market Size, By Component, 2016-2026 (USD Million)
10.5.9.2 Market Size, By Type, 2016-2026 (USD Million)
10.5.9.3 Market Size, By Application, 2016-2026 (USD Million)
10.5.9.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.5.9.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.5.9.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.5.10 Argentina
10.5.10.1 Market Size, By Component, 2016-2026 (USD Million)
10.5.10.2 Market Size, By Type, 2016-2026 (USD Million)
10.5.10.3 Market Size, By Application, 2016-2026 (USD Million)
10.5.10.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.5.10.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.5.10.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.6 MEA
10.6.1 Market Size, By Country 2016-2026 (USD Million)
10.6.2 Market Size, By Component, 2016-2026 (USD Million)
10.6.3 Market Size, By Type, 2016-2026 (USD Million)
10.6.4 Market Size, By Application, 2016-2026 (USD Million)
10.6.5 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.6.6 Market Size, By Organization Size, 2016-2026 (USD Million)
10.6.7 Market Size, By End-Users, 2016-2026 (USD Million)
10.6.8 Saudi Arabia
10.6.8.1 Market Size, By Component, 2016-2026 (USD Million)
10.6.8.2 Market Size, By Type, 2016-2026 (USD Million)
10.6.8.3 Market Size, By Application, 2016-2026 (USD Million)
10.6.8.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.6.8.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.6.8.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.6.9 UAE
10.6.9.1 Market Size, By Component, 2016-2026 (USD Million)
10.6.9.2 Market Size, By Type, 2016-2026 (USD Million)
10.6.9.3 Market Size, By Application, 2016-2026 (USD Million)
10.6.9.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.6.9.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.6.9.6 Market Size, By End-Users, 2016-2026 (USD Million)
10.6.10 South Africa
10.6.10.1 Market Size, By Component, 2016-2026 (USD Million)
10.6.10.2 Market Size, By Type, 2016-2026 (USD Million)
10.6.10.3 Market Size, By Application, 2016-2026 (USD Million)
10.6.10.4 Market Size, By Deployment Mode, 2016-2026 (USD Million)
10.6.10.5 Market Size, By Organization Size, 2016-2026 (USD Million)
10.6.10.6 Market Size, By End-Users, 2016-2026 (USD Million)
Chapter 11 Company Landscape
11.1 Competitive Analysis, 2020
11.2 3M
11.2.1 Company Overview
11.2.2 Financial Analysis
11.2.3 Strategic Positioning
11.2.4 Info Graphic Analysis
11.3 Apple
11.3.1 Company Overview
11.3.2 Financial Analysis
11.3.3 Strategic Positioning
11.3.4 Info Graphic Analysis
11.4 Google
11.4.1 Company Overview
11.4.2 Financial Analysis
11.4.3 Strategic Positioning
11.4.4 Info Graphic Analysis
11.5 Microsoft
11.5.1 Company Overview
11.5.2 Financial Analysis
11.5.3 Strategic Positioning
11.5.4 Info Graphic Analysis
11.6 A3logics
11.6.1 Company Overview
11.6.2 Financial Analysis
11.6.3 Strategic Positioning
11.6.4 Info Graphic Analysis
11.7 AlchemyAPI
11.7.1 Company Overview
11.7.2 Financial Analysis
11.7.3 Strategic Positioning
11.7.4 Info Graphic Analysis
11.8 Apixio
11.8.1 Company Overview
11.8.2 Financial Analysis
11.8.3 Strategic Positioning
11.8.4 Info Graphic Analysis
11.9 Aylien
11.9.1 Company Overview
11.9.2 Financial Analysis
11.9.3 Strategic Positioning
11.9.4 Info Graphic Analysis
11.10 Dolbey Systems
11.10.1 Company Overview
11.10.2 Financial Analysis
11.10.3 Strategic Positioning
11.10.4 Info Graphic Analysis
11.11 Fluxifi
11.11.1 Company Overview
11.11.2 Financial Analysis
11.11.3 Strategic Positioning
11.11.4 Info Graphic Analysis
11.12 HP
11.12.1 Company Overview
11.12.2 Financial Analysis
11.12.3 Strategic Positioning
11.12.4 Info Graphic Analysis
11.13 IBM
11.13.1 Company Overview
11.13.2 Financial Analysis
11.13.3 Strategic Positioning
11.13.4 Info Graphic Analysis
11.14 Linguamatics
11.14.1 Company Overview
11.14.2 Financial Analysis
11.14.3 Strategic Positioning
11.14.4 Info Graphic Analysis
11.15 Mmodal
11.15.1 Company Overview
11.15.2 Financial Analysis
11.15.3 Strategic Positioning
11.15.4 Info Graphic Analysis
11.16 Netbase
11.16.1 Company Overview
11.16.2 Financial Analysis
11.16.3 Strategic Positioning
11.16.4 Info Graphic Analysis
11.17 Nuance Communication
11.17.1 Company Overview
11.17.2 Financial Analysis
11.17.3 Strategic Positioning
11.17.4 Info Graphic Analysis
11.18 SAS Institute
11.18.1 Company Overview
11.18.2 Financial Analysis
11.18.3 Strategic Positioning
11.18.4 Info Graphic Analysis
11.19 Textalytics
11.19.1 Company Overview
11.19.2 Financial Analysis
11.19.3 Strategic Positioning
11.19.4 Info Graphic Analysis
11.20 Verint Systems
11.20.1 Company Overview
11.20.2 Financial Analysis
11.20.3 Strategic Positioning
11.20.4 Info Graphic Analysis
11.21 Other Compnaies
11.21.1 Company Overview
11.21.2 Financial Analysis
11.21.3 Strategic Positioning
11.21.4 Info Graphic Analysis
The Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market has been studied from the year 2019 till 2026. However, the CAGR provided in the report is from the year 2021 to 2026. The research methodology involved three stages: Desk research, Primary research, and Analysis & Output from the entire research process.
The desk research involved a robust background study which meant referring to paid and unpaid databases to understand the market dynamics; mapping contracts from press releases; identifying the key players in the market, studying their product portfolio, competition level, annual reports/SEC filings & investor presentations; and learning the demand and supply-side analysis for the Natural Language Processing (NLP) in Healthcare and Life Sciences Market.
The primary research activity included telephonic conversations with more than 50 tier 1 industry consultants, distributors, and end-use product manufacturers.
Finally, based on the above thorough research process, an in-depth analysis was carried out considering the following aspects: market attractiveness, current & future market trends, market share analysis, SWOT analysis of the company and customer analytics.
Frequently Asked Questions
![Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market Size, Trends & Analysis - Forecasts to 2026 By Component (Standalone Solutions and Services [Support & Maintenance and Professional Services]), By Type (Rule-Based Natural Language Processing, Statistical Natural Language Processing, and Hybrid Natural Language Processing), By Application (Interactive Voice Response (IVR), Pattern & Image Recognition, Auto Coding, Classification & Categorization, Text & Speech Analytics, and Others (Information Extraction and Report Generation), By Deployment Mode (Cloud and On-premises), By Organization Size (Large Enterprise and Small and Medium-sized Enterprises (SMEs)), By End-Users ( NLP for Physicians, NLP for Researchers, NLP for Patients, and NLP for Clinical Operators), By Region (North America, Asia Pacific, Europe, Latin America, Middle East & Africa); End-User Landscape, Company Market Share Analysis, and Competitor Analysis](https://www.globalmarketestimates.com/images/cat/Healthcare.png)
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