The NLP in healthcare and life sciences market size was estimated at US$ 2.39 billion in 2022 it is predicted to grow at a CAGR of 27.3% from 2023 to 2032 to reach around US$ 26.75 billion by the end of 2032.
The NLP in healthcare and life sciences market report offers an exclusive study of the present state expected at the market dynamics, opportunities, market scheme, growth analysis and regional outlook. The report presents energetic visions to conclude and study the market size, market aspiration, and competitive environment. The research also focuses on the important achievements of the market, research & development, and regional (country by country) growth of the leading vendors operating in the market
The study offers intricate dynamics about different aspects of the global NLP in healthcare and life sciences market, which aids companies operating in the market in making strategies development decisions. The study also elaborates on remarkable changes that are highly anticipated to configure growth of the global NLP in healthcare and life sciences market during the forecast period. It also includes a key indicator analysis that highlights growth prospects of this market and approximate statistics related to growth of the market in terms of value (US$ Bn) and volume (tons).
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Report Scope of the NLP in Healthcare and Life Sciences Market
| Report Coverage | Details |
| Market Size in 2022 | USD 2.39 billion |
| Revenue Forecast by 2032 | USD 26.75 billion |
| Growth rate from 2023 to 2032 | CAGR of 27.3% |
| Base Year | 2022 |
| Forecast Period | 2023 to 2032 |
| Regions Covered | North America, Europe, Asia Pacific, Latin America, Middle East & Africa |
| Companies Covered | 3M Company, Alphabet Inc., Amazon.com, Inc., Averbis GmbH, Cerner Corporation, Clinithink, Conversica Inc., Dolbey Systems, Inc., Health Fidelity, Inc., Hewlett Packard Enterprise Development LP, IBM Corporation, Inovalon, IQVIA Holdings Inc., Lexalytics, Microsoft Corporation, SparkCognition, and Wave Health Technologies. |
This study covers an elaborate segmentation of the global NLP in healthcare and life sciences market, along with important information and a competition outlook. The report mentions company profiles of players that are currently influence the global NLP in healthcare and life sciences market, wherein various developments, expansions, and winning strategies practiced and execute by leading players have been presented in detail.
NLP in Healthcare and Life Sciences Market Segmentations:
| By Component | By NLP Type | By Deployment Mode | By Organization Size |
| Solutions
Services |
Rule-based Natural Language Processing
Statistical Natural Language Processing Hybrid Natural Language Processing |
On-premises
Cloud |
Large Enterprises
SMEs |
| By Application | By NLP Technique | By End User |
| Sentiment Analysis
Drug Discovery Clinical Trial Matching Risk & Compliance Management Dictation & EMR Implications Automated Registry Reporting AI Chatbots & Virtual Scribe Other |
Optical Character Recognition (OCR)
Interactive Voice Response (IVR) Sentiment Analysis Text & Speech Analytics Image & Pattern Recognition Text Summarization & Categorization Other |
Public Health & Government Agencies
Medical Devices Healthcare Insurance Pharmaceuticals Other |
Research Methodology
The research methodology acquire by analysts for assemble the global NLP in healthcare and life sciences market report is based on detailed primary as well as secondary research. With the help of in-depth insights of the market-affiliated information that is obtained and legitimated by market-admissible resources, analysts have offered riveting observations and authentic forecasts for the global market.
During the primary research phase, analysts interviewed market stakeholders, investors, brand managers, vice presidents, and sales and marketing managers. Based on data obtained through interviews of genuine resources, analysts have emphasized the changing scenario of the global market.
For secondary research, analysts study numerous annual report declaration, white papers, market association declaration, and company websites to obtain the necessary understanding of the global NLP in healthcare and life sciences market.
TABLE OF CONTENT
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. Market Dynamics Analysis and Trends
5.1. Market Dynamics
5.1.1. Market Drivers
5.1.2. Market Restraints
5.1.3. Market Opportunities
5.2. Porter’s Five Forces Analysis
5.2.1. Bargaining power of suppliers
5.2.2. Bargaining power of buyers
5.2.3. Threat of substitute
5.2.4. Threat of new entrants
5.2.5. Degree of competition
Chapter 6. Competitive Landscape
6.1.1. Company Market Share/Positioning Analysis
6.1.2. Key Strategies Adopted by Players
6.1.3. Vendor Landscape
6.1.3.1. List of Suppliers
6.1.3.2. List of Buyers
Chapter 7. Global NLP in Healthcare and Life Sciences Market, By Component
7.1. NLP in Healthcare and Life Sciences Market, by Component, 2023-2032
7.1.1. Solutions
7.1.1.1. Market Revenue and Forecast (2020-2032)
7.1.2. Services
7.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 8. Global NLP in Healthcare and Life Sciences Market, By NLP Type
8.1. NLP in Healthcare and Life Sciences Market, by NLP Type, 2023-2032
8.1.1. Rule-based Natural Language Processing
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Statistical Natural Language Processing
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Hybrid Natural Language Processing
8.1.3.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global NLP in Healthcare and Life Sciences Market, By Deployment Mode
9.1. NLP in Healthcare and Life Sciences Market, by Deployment Mode, 2023-2032
9.1.1. On-premises
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Cloud
9.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global NLP in Healthcare and Life Sciences Market, By Organization Size
10.1. NLP in Healthcare and Life Sciences Market, by Organization Size, 2023-2032
10.1.1. Large Enterprises
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. SMEs
10.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global NLP in Healthcare and Life Sciences Market, By Application
11.1. NLP in Healthcare and Life Sciences Market, by Application, 2023-2032
11.1.1. Sentiment Analysis
11.1.1.1. Market Revenue and Forecast (2020-2032)
11.1.2. Drug Discovery
11.1.2.1. Market Revenue and Forecast (2020-2032)
11.1.3. Clinical Trial Matching
11.1.3.1. Market Revenue and Forecast (2020-2032)
11.1.4. Risk & Compliance Management
11.1.4.1. Market Revenue and Forecast (2020-2032)
11.1.5. Dictation & EMR Implications
11.1.5.1. Market Revenue and Forecast (2020-2032)
11.1.6. Automated Registry Reporting
11.1.6.1. Market Revenue and Forecast (2020-2032)
11.1.7. AI Chatbots & Virtual Scribe
11.1.7.1. Market Revenue and Forecast (2020-2032)
11.1.8. Others
11.1.8.1. Market Revenue and Forecast (2020-2032)
Chapter 12. Global NLP in Healthcare and Life Sciences Market, By NLP Technique
12.1. NLP in Healthcare and Life Sciences Market, by NLP Technique, 2023-2032
12.1.1. Optical Character Recognition (OCR)
12.1.1.1. Market Revenue and Forecast (2020-2032)
12.1.2. Interactive Voice Response (IVR)
12.1.2.1. Market Revenue and Forecast (2020-2032)
12.1.3. Sentiment Analysis
12.1.3.1. Market Revenue and Forecast (2020-2032)
12.1.4. Text & Speech Analytics
12.1.4.1. Market Revenue and Forecast (2020-2032)
12.1.5. Image & Pattern Recognition
12.1.5.1. Market Revenue and Forecast (2020-2032)
12.1.6. Text Summarization & Categorization
12.1.6.1. Market Revenue and Forecast (2020-2032)
12.1.7. Others
12.1.7.1. Market Revenue and Forecast (2020-2032)
Chapter 13. Global NLP in Healthcare and Life Sciences Market, By End User
13.1. NLP in Healthcare and Life Sciences Market, by End User, 2023-2032
13.1.1. Public Health & Government Agencies
13.1.1.1. Market Revenue and Forecast (2020-2032)
13.1.2. Medical Devices
13.1.2.1. Market Revenue and Forecast (2020-2032)
13.1.3. Healthcare Insurance
13.1.3.1. Market Revenue and Forecast (2020-2032)
13.1.4. Pharmaceuticals
13.1.4.1. Market Revenue and Forecast (2020-2032)
13.1.5. Others
13.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 14. Global NLP in Healthcare and Life Sciences Market, Regional Estimates and Trend Forecast
14.1. North America
14.1.1. Market Revenue and Forecast, by Component (2020-2032)
14.1.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.1.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.1.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.1.5. Market Revenue and Forecast, by Application (2020-2032)
14.1.6. Market Revenue and Forecast, by End User (2020-2032)
14.1.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.1.8. U.S.
14.1.8.1. Market Revenue and Forecast, by Component (2020-2032)
14.1.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.1.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.1.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.1.8.5. Market Revenue and Forecast, by Application (2020-2032)
14.1.8.6. Market Revenue and Forecast, by End User (2020-2032)
14.1.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.1.9. Rest of North America
14.1.9.1. Market Revenue and Forecast, by Component (2020-2032)
14.1.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.1.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.1.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.1.9.5. Market Revenue and Forecast, by Application (2020-2032)
14.1.9.6. Market Revenue and Forecast, by End User (2020-2032)
14.1.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.2. Europe
14.2.1. Market Revenue and Forecast, by Component (2020-2032)
14.2.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.2.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.2.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.2.5. Market Revenue and Forecast, by Application (2020-2032)
14.2.6. Market Revenue and Forecast, by End User (2020-2032)
14.2.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.2.8. UK
14.2.8.1. Market Revenue and Forecast, by Component (2020-2032)
14.2.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.2.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.2.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.2.8.5. Market Revenue and Forecast, by Application (2020-2032)
14.2.8.6. Market Revenue and Forecast, by End User (2020-2032)
14.2.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.2.9. Germany
14.2.9.1. Market Revenue and Forecast, by Component (2020-2032)
14.2.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.2.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.2.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.2.9.5. Market Revenue and Forecast, by Application (2020-2032)
14.2.9.6. Market Revenue and Forecast, by End User (2020-2032)
14.2.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.2.10. France
14.2.10.1. Market Revenue and Forecast, by Component (2020-2032)
14.2.10.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.2.10.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.2.10.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.2.10.5. Market Revenue and Forecast, by Application (2020-2032)
14.2.10.6. Market Revenue and Forecast, by End User (2020-2032)
14.2.10.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.2.11. Rest of Europe
14.2.11.1. Market Revenue and Forecast, by Component (2020-2032)
14.2.11.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.2.11.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.2.11.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.2.11.5. Market Revenue and Forecast, by Application (2020-2032)
14.2.11.6. Market Revenue and Forecast, by End User (2020-2032)
14.2.11.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.3. APAC
14.3.1. Market Revenue and Forecast, by Component (2020-2032)
14.3.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.3.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.3.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.3.5. Market Revenue and Forecast, by Application (2020-2032)
14.3.6. Market Revenue and Forecast, by End User (2020-2032)
14.3.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.3.8. India
14.3.8.1. Market Revenue and Forecast, by Component (2020-2032)
14.3.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.3.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.3.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.3.8.5. Market Revenue and Forecast, by Application (2020-2032)
14.3.8.6. Market Revenue and Forecast, by End User (2020-2032)
14.3.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.3.9. China
14.3.9.1. Market Revenue and Forecast, by Component (2020-2032)
14.3.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.3.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.3.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.3.9.5. Market Revenue and Forecast, by Application (2020-2032)
14.3.9.6. Market Revenue and Forecast, by End User (2020-2032)
14.3.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.3.10. Japan
14.3.10.1. Market Revenue and Forecast, by Component (2020-2032)
14.3.10.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.3.10.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.3.10.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.3.10.5. Market Revenue and Forecast, by Application (2020-2032)
14.3.10.6. Market Revenue and Forecast, by End User (2020-2032)
14.3.10.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.3.11. Rest of APAC
14.3.11.1. Market Revenue and Forecast, by Component (2020-2032)
14.3.11.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.3.11.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.3.11.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.3.11.5. Market Revenue and Forecast, by Application (2020-2032)
14.3.11.6. Market Revenue and Forecast, by End User (2020-2032)
14.3.11.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.4. MEA
14.4.1. Market Revenue and Forecast, by Component (2020-2032)
14.4.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.4.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.4.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.4.5. Market Revenue and Forecast, by Application (2020-2032)
14.4.6. Market Revenue and Forecast, by End User (2020-2032)
14.4.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.4.8. GCC
14.4.8.1. Market Revenue and Forecast, by Component (2020-2032)
14.4.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.4.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.4.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.4.8.5. Market Revenue and Forecast, by Application (2020-2032)
14.4.8.6. Market Revenue and Forecast, by End User (2020-2032)
14.4.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.4.9. North Africa
14.4.9.1. Market Revenue and Forecast, by Component (2020-2032)
14.4.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.4.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.4.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.4.9.5. Market Revenue and Forecast, by Application (2020-2032)
14.4.9.6. Market Revenue and Forecast, by End User (2020-2032)
14.4.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.4.10. South Africa
14.4.10.1. Market Revenue and Forecast, by Component (2020-2032)
14.4.10.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.4.10.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.4.10.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.4.10.5. Market Revenue and Forecast, by Application (2020-2032)
14.4.10.6. Market Revenue and Forecast, by End User (2020-2032)
14.4.10.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.4.11. Rest of MEA
14.4.11.1. Market Revenue and Forecast, by Component (2020-2032)
14.4.11.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.4.11.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.4.11.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.4.11.5. Market Revenue and Forecast, by Application (2020-2032)
14.4.11.6. Market Revenue and Forecast, by End User (2020-2032)
14.4.11.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.5. Latin America
14.5.1. Market Revenue and Forecast, by Component (2020-2032)
14.5.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.5.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.5.5. Market Revenue and Forecast, by Application (2020-2032)
14.5.6. Market Revenue and Forecast, by End User (2020-2032)
14.5.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.5.8. Brazil
14.5.8.1. Market Revenue and Forecast, by Component (2020-2032)
14.5.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.5.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.5.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.5.8.5. Market Revenue and Forecast, by Application (2020-2032)
14.5.8.6. Market Revenue and Forecast, by End User (2020-2032)
14.5.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
14.5.9. Rest of LATAM
14.5.9.1. Market Revenue and Forecast, by Component (2020-2032)
14.5.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)
14.5.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)
14.5.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)
14.5.9.5. Market Revenue and Forecast, by Application (2020-2032)
14.5.9.6. Market Revenue and Forecast, by End User (2020-2032)
14.5.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)
Chapter 15. Company Profiles
15.1. 3M Company
15.1.1. Company Overview
15.1.2. Product Offerings
15.1.3. Financial Performance
15.1.4. Recent Initiatives
15.2. Alphabet Inc.
15.2.1. Company Overview
15.2.2. Product Offerings
15.2.3. Financial Performance
15.2.4. Recent Initiatives
15.3. Amazon.com, Inc.
15.3.1. Company Overview
15.3.2. Product Offerings
15.3.3. Financial Performance
15.3.4. Recent Initiatives
15.4. Averbis GmbH
15.4.1. Company Overview
15.4.2. Product Offerings
15.4.3. Financial Performance
15.4.4. Recent Initiatives
15.5. Cerner Corporation
15.5.1. Company Overview
15.5.2. Product Offerings
15.5.3. Financial Performance
15.5.4. Recent Initiatives
15.6. Clinithink
15.6.1. Company Overview
15.6.2. Product Offerings
15.6.3. Financial Performance
15.6.4. Recent Initiatives
15.7. Conversica Inc.
15.7.1. Company Overview
15.7.2. Product Offerings
15.7.3. Financial Performance
15.7.4. Recent Initiatives
15.8. Dolbey Systems, Inc.
15.8.1. Company Overview
15.8.2. Product Offerings
15.8.3. Financial Performance
15.8.4. Recent Initiatives
15.9. Health Fidelity, Inc.
15.9.1. Company Overview
15.9.2. Product Offerings
15.9.3. Financial Performance
15.9.4. Recent Initiatives
15.10. Hewlett Packard Enterprise Development LP
15.10.1. Company Overview
15.10.2. Product Offerings
15.10.3. Financial Performance
15.10.4. Recent Initiatives
Chapter 16. Research Methodology
16.1. Primary Research
16.2. Secondary Research
16.3. Assumptions
Chapter 17. Appendix
17.1. About Us
17.2. Glossary of Terms
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