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Global NLP in Healthcare and Life Sciences Market to reach USD 5.1 billion by 2027.

Global NLP in Healthcare and Life Sciences Market by Component (Solutions and Services), NLP Type (Rule-based, Statistical, and Hybrid), Application (IVR, Predictive Risk Analytics), Deployment mode (Cloud, on premises), Organization Size (Large enterprises, medium and small enterprises), End User (NLP for Physician, NLP for Patients, NLP for Researchers, NLP for Clinical Operators), Regional Forecasts 2021-2027

Product Code: HLSHIT-62917534
Publish Date: 26-08-2021
Page: 200

Global NLP in Healthcare and Life Sciences Market is valued approximately at USD 1.5 billion in 2020 and is anticipated to grow with a healthy growth rate of more than 19% over the forecast period 2021-2027. Natural language processing for health and life sciences is an area that provides computers the capacity to interpret human speech, artificial intelligence, and computer linguistics as they communicate. It enables a range of semi-structured and unstructured textual documents to be created, managed and used for clinical and medical research. NLP applications for healthcare and life sciences cover huge data processing, using advanced IT technology, automated voice recognition, machine translation and dialogue systems. The market is driven by rising demand of predictive analytics technology and growing demand for improving EHR data usability. For instance, as per Statista, the predictive analytics technology market was over USD 6 billion in total revenue. Furthermore, by 2022, the annual revenues of the market are anticipated to reach about $11 billion as more and more organizations utilize predictive analysis techniques for everything from fraud detection to medical diagnostics. Also, increasing private players initiatives in the NLP in healthcare and life sciences boost the market growth in the forecasting years. For instance, Google collaborated with HCA Healthcare in May 2021, establishing a new data analysis platform which will utilize data from 32 million monthly conference with patients within the health system. However, specific medical sub-languages and poor input data quality may impede market growth over the forecast period of 2021-2027.

Geographically, North America is dominating the market owing to rapid developments in IT infrastructure across healthcare sectors, favorable approach of government laws, start-up financing, a well-established player presence and the willingness from companies to deploy solutions based on ML and NLP, the area has seen ideal conditions for the NLP growth in healthcare and life sciences.

Major market player included in this report are:
Wave Health Technologies
Caption Health
Oncora Medical
ForeSee Medical
CloudMedx
Google Inc.
Gnani.ai
IBM
IQVIA Company
Press Ganey

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:
Solution
Services
By Deployment mode:
Cloud
On-premises
By Organization size:
Large enterprises
Small and medium-sized enterprises
By NLP type:
Rule-based
Statistical
Hybrid
By Application:
IVR
Pattern and Image Recognition
Summarization and Categorization
Text and Speech Analytics
Predictive Risk Analytics
Reporting and Visualization
Other Applications
By End use:
NLP for Physician
NLP for Patients
NLP for Researchers
NLP for Clinical Operators
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027.

Target Audience of the Global NLP in Healthcare and Life Sciences Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. NLP in Healthcare and Life Sciences Market, by Region, 2019-2027 (USD Billion)
1.2.2. NLP in Healthcare and Life Sciences Market, by Component, 2019-2027 (USD Billion)
1.2.3. NLP in Healthcare and Life Sciences Market, by Deployment Mode, 2019-2027 (USD Billion)
1.2.4. NLP in Healthcare and Life Sciences Market, by NLP type, 2019-2027 (USD Billion)
1.2.5. NLP in Healthcare and Life Sciences Market, by Organization size, 2019-2027 (USD Billion)
1.2.6. NLP in Healthcare and Life Sciences Market, by Application, 2019-2027 (USD Billion)
1.2.7. NLP in Healthcare and Life Sciences Market, by End use, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global NLP in Healthcare and Life Sciences Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global NLP in Healthcare and Life Sciences Market Dynamics
3.1. NLP in Healthcare and Life Sciences Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Rising demand for predictive analytics technology
3.1.1.2. Growing demand for improving EHR data usability
3.1.2. Market Restraint
3.1.2.1. Specific medical sub-languages and poor input data quality
3.1.2.2. Limited access to clinical data
3.1.3. Market Opportunities
3.1.3.1. Rising demand for NLP systems programmed to understand the context of medical records
3.1.3.2. Ensemble NLP systems to boost phenotyping capabilities
Chapter 4. Global NLP in Healthcare and Life Sciences Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global NLP in Healthcare and Life Sciences Market, by Component
5.1. Market Snapshot
5.2. Global NLP in Healthcare and Life Sciences Market by Component, Performance – Potential Analysis
5.3. Global NLP in Healthcare and Life Sciences Market Estimates & Forecasts by Component 2018-2027 (USD Billion)
5.4. NLP in Healthcare and Life Sciences Market , Sub Segment Analysis
5.4.1. Solution
5.4.2. Services
Chapter 6. Global NLP in Healthcare and Life Sciences Market, by Deployment mode
6.1. Market Snapshot
6.2. Global NLP in Healthcare and Life Sciences Market by Deployment mode , Performance – Potential Analysis
6.3. Global NLP in Healthcare and Life Sciences Market Estimates & Forecasts by Deployment mode 2018-2027 (USD Billion)
6.4. NLP in Healthcare and Life Sciences Market , Sub Segment Analysis
6.4.1. Cloud
6.4.2. On-premises
Chapter 7. Global NLP in Healthcare and Life Sciences Market, by Organization size
7.1. Market Snapshot
7.2. Global NLP in Healthcare and Life Sciences Market by Organization size , Performance – Potential Analysis
7.3. Global NLP in Healthcare and Life Sciences Market Estimates & Forecasts by Organization size 2018-2027 (USD Billion)
7.4. NLP in Healthcare and Life Sciences Market , Sub Segment Analysis
7.4.1. Large enterprises
7.4.2. Small and medium-sized enterprises
Chapter 8. Global NLP in Healthcare and Life Sciences Market, by NLP type
8.1. Market Snapshot
8.2. Global NLP in Healthcare and Life Sciences Market by NLP type , Performance – Potential Analysis
8.3. Global NLP in Healthcare and Life Sciences Market Estimates & Forecasts by NLP type 2018-2027 (USD Billion)
8.4. NLP in Healthcare and Life Sciences Market , Sub Segment Analysis
8.4.1. Rule-based
8.4.2. Statistical
8.4.3. Hybrid
Chapter 9. Global NLP in Healthcare and Life Sciences Market, by End use
9.1. Market Snapshot
9.2. Global NLP in Healthcare and Life Sciences Market by End Use, Performance – Potential Analysis
9.3. Global NLP in Healthcare and Life Sciences Market Estimates & Forecasts by End Use 2018-2027 (USD Billion)
9.4. NLP in Healthcare and Life Sciences Market , Sub Segment Analysis
9.4.1. NLP for Physician
9.4.2. NLP for Patients
9.4.3. NLP for Researchers
9.4.4. NLP for Clinical Operators
Chapter 10. Global NLP in Healthcare and Life Sciences Market, by Application
10.1. Market Snapshot
10.2. Global NLP in Healthcare and Life Sciences Market by Application, Performance – Potential Analysis
10.3. Global NLP in Healthcare and Life Sciences Market Estimates & Forecasts by Application 2018-2027 (USD Billion)
10.4. NLP in Healthcare and Life Sciences Market , Sub Segment Analysis
10.4.1. IVR
10.4.2. Pattern and Image Recognition
10.4.3. Summarization and Categorization
10.4.4. Text and Speech Analytics
10.4.5. Predictive Risk Analytics
10.4.6. Reporting and Visualization
10.4.7. Other Applications
Chapter 11. Global NLP in Healthcare and Life Sciences Market, Regional Analysis
11.1. NLP in Healthcare and Life Sciences Market , Regional Market Snapshot
11.2. North America NLP in Healthcare and Life Sciences Market
11.2.1. U.S. NLP in Healthcare and Life Sciences Market
11.2.1.1. Component breakdown estimates & forecasts, 2018-2027
11.2.1.2. Deployment mode breakdown estimates & forecasts, 2018-2027
11.2.1.3. Organizational size breakdown estimates & forecasts, 2018-2027
11.2.1.4. NLP type breakdown estimates & forecasts, 2018-2027
11.2.1.5. End use breakdown estimates & forecasts, 2018-2027
11.2.1.6. Application breakdown estimates & forecasts, 2018-2027
11.2.2. Canada NLP in Healthcare and Life Sciences Market
11.3. Europe NLP in Healthcare and Life Sciences Market Snapshot
11.3.1. U.K. NLP in Healthcare and Life Sciences Market
11.3.2. Germany NLP in Healthcare and Life Sciences Market
11.3.3. France NLP in Healthcare and Life Sciences Market
11.3.4. Spain NLP in Healthcare and Life Sciences Market
11.3.5. Italy NLP in Healthcare and Life Sciences Market
11.3.6. Rest of Europe NLP in Healthcare and Life Sciences Market
11.4. Asia-Pacific NLP in Healthcare and Life Sciences Market Snapshot
11.4.1. China NLP in Healthcare and Life Sciences Market
11.4.2. India NLP in Healthcare and Life Sciences Market
11.4.3. Japan NLP in Healthcare and Life Sciences Market
11.4.4. Australia NLP in Healthcare and Life Sciences Market
11.4.5. South Korea NLP in Healthcare and Life Sciences Market
11.4.6. Rest of Asia Pacific NLP in Healthcare and Life Sciences Market
11.5. Latin America NLP in Healthcare and Life Sciences Market Snapshot
11.5.1. Brazil NLP in Healthcare and Life Sciences Market
11.5.2. Mexico NLP in Healthcare and Life Sciences Market
11.6. Rest of The World NLP in Healthcare and Life Sciences Market
Chapter 12. Competitive Intelligence
12.1. Top Market Strategies
12.2. Company Profiles
12.2.1. Wave Health Technologies
12.2.1.1. Key Information
12.2.1.2. Overview
12.2.1.3. Financial (Subject to Data Availability)
12.2.1.4. Product Summary
12.2.1.5. Recent Developments
12.2.2. Caption Health
12.2.3. Oncora Medical
12.2.4. ForeSee Medical
12.2.5. CloudMedx
12.2.6. Google Inc.
12.2.7. Gnani.ai
12.2.8. IBM
12.2.9. IQVIA Company
12.2.10. Press Ganey
Chapter 13. Research Process
13.1. Research Process
13.1.1. Data Mining
13.1.2. Analysis
13.1.3. Market Estimation
13.1.4. Validation
13.1.5. Publishing
13.2. Research Attributes
13.3. Research Assumption

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Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
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