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As per Intent Market Research, the NLP in Healthcare & Life Sciences Market was valued at USD 2.5 billion in 2023-e and will surpass USD 19.8 billion by 2030; growing at a CAGR of 34.4% during 2024 - 2030.
The report focuses on estimating the current market potential in terms of the total addressable market for all the segments, sub-segments, and regions. In the process, all the high-growth and upcoming technologies were identified and analyzed to measure their impact on the current and future market. The report also identifies the key stakeholders, their business gaps, and their purchasing behavior. This information is essential for developing effective marketing strategies and creating products or services that meet the needs of the target market. The report also covers a detailed analysis of the competitive landscape which includes major players, their recent developments, growth strategies, product benchmarking, and manufacturing operations among others. Also, brief insights on start-up ecosystem and emerging companies are also included as part of this report.
The report will help you answer some of the most critical questions in the NLP in Healthcare & Life Sciences Market. A few of them are as follows:
Report Features |
Description |
Market Size (2023-e) |
USD 2.5 billion |
Forecasted Value (2030) |
USD 19.8 billion |
CAGR (2024-2030) |
34.4% |
Base Year for Estimation |
2023-e |
Historic Year |
2022 |
Forecast Period |
2024-2030 |
Report Coverage |
Market Forecast, Market Dynamics, Competitive Landscape, Recent Developments |
Segments Covered |
NLP in Healthcare & Life Sciences Market By Application (Clinical Decision Support, Drug Discovery & Development, Clinical Trial Matching, Electronic Health Record Search & Retrieval, Healthcare Chatbots & Virtual Assistants, Clinical Documentation Processing, Medical Imaging), By Offering (Solutions, Services), By NLP Type (Rule-Based, Hybrid, Statistical, Neural), By End-Use (Healthcare Researchers, Pharmaceuticals & Biotech Companies, Health Insurance & Payer Professionals, Healthcare Administrators), By NLP Technique (Name Entity Recognition, Optical Character Recognition, Sentimental Analysis, Text Classification, Topic Modeling, Image & Pattern Recognition) |
Regional Analysis |
North America (US, Canada), Europe (Germany, France, UK, Spain, Italy & Rest of Europe), Asia Pacific (China, Japan, South Korea, India, and rest of Asia Pacific), Latin America (Brazil, Mexico, Argentina, & Rest of Latin America), Middle East & Africa (Saudi Arabia, South Africa, Turkey, United Arab Emirates, & Rest of MEA) |
Customization Scope |
Customization for segments, region/country-level will be provided. Moreover, additional customization can be done based on the requirements |
1.Introduction |
1.1.Market Definition |
1.2.Scope of the Study |
1.3.Research Assumptions |
1.4.Study Limitations |
2.Research Methodology |
2.1.Research Approach |
2.1.1.Top-Down Method |
2.1.2.Bottom-Up Method |
2.1.3.Factor Impact Analysis |
2.2.Insights & Data Collection Process |
2.2.1.Secondary Research |
2.2.2.Primary Research |
2.3.Data Mining Process |
2.3.1.Data Analysis |
2.3.2.Data Validation and Revalidation |
2.3.3.Data Triangulation |
3.Executive Summary |
3.1.Major Markets & Segments |
3.2.Highest Growing Regions and Respective Countries |
3.3.Impact of Growth Drivers & Inhibitors |
3.4.Regulatory Overview by Country |
4.NLP in Healthcare & Life Sciences Market, by Offering (Market Size & Forecast: USD Billion, 2024 – 2030) |
4.1.Solutions |
4.1.1.Type |
4.1.1.1.Software |
4.1.1.2.Platforms |
4.1.2.Deployment Mode |
4.1.2.1.CLoud |
4.1.2.2.On-premises |
4.2.Services |
4.2.1.Professional Services |
4.2.1.1.Training & Consulting Services |
4.2.1.2.System Integration & Implementation |
4.2.1.3.Support & Maintenance |
4.2.2.Managed Services |
5.NLP in Healthcare & Life Sciences Market, by NLP Type (Market Size & Forecast: USD Billion, 2024 – 2030) |
5.1.Hybrid |
5.2.Statistical |
5.3.Rule-Based |
5.4.Neural |
6.NLP in Healthcare & Life Sciences Market, by NLP Technique (Market Size & Forecast: USD Billion, 2024 – 2030) |
6.1.Text Classification |
6.2.Optical Character Recognition |
6.3.Named Entity Recognition |
6.4.Sentiment Analysis |
6.5.Image & Pattern Recognition |
6.6.Topic Modeling |
6.7.Others |
7.NLP in Healthcare & Life Sciences Market, by Application (Market Size & Forecast: USD Billion, 2024 – 2030) |
7.1.Clinical Decision Support |
7.2.Drug Discovery & Development |
7.3.Clinical Trial Matching |
7.4.Electronic Health Record Search & Retrieval |
7.5.Healthcare Chatbots & Virtual Assistants |
7.6.Clinical Documentation Processing |
7.7.Medical Imaging |
7.8.Others |
8.NLP in Healthcare & Life Sciences Market, by End Use (Market Size & Forecast: USD Billion, 2024 – 2030) |
8.1.Healthcare Researchers |
8.2.Clinical Practitioners |
8.3.Healthcare Administrators |
8.4.Pharmaceutical & Biotech Companies |
8.5.Health Insurance & Payer Professionals |
8.6.Others |
9.Regional Analysis (Market Size & Forecast: USD Billion, 2024 – 2030) |
9.1.Regional Overview |
9.2.North America |
9.2.1.Regional Trends & Growth Drivers |
9.2.2.Barriers & Challenges |
9.2.3.Opportunities |
9.2.4.Factor Impact Analysis |
9.2.5.Technology Trends |
9.2.6.North America NLP in Healthcare & Life Sciences Market, by Offering |
9.2.7.North America NLP in Healthcare & Life Sciences Market, by Type |
9.2.8.North America NLP in Healthcare & Life Sciences Market, by Technique |
9.2.9.North America NLP in Healthcare & Life Sciences Market, by Application |
9.2.10.North America NLP in Healthcare & Life Sciences Market, by End Use |
*Similar segmentation will be provided at each regional level |
9.3.By Country |
9.3.1.US |
9.3.1.1.US NLP in Healthcare & Life Sciences Market, by Offering |
9.3.1.2.US NLP in Healthcare & Life Sciences Market, by Type |
9.3.1.3.US NLP in Healthcare & Life Sciences Market, by Technique |
9.3.1.4.US NLP in Healthcare & Life Sciences Market, by Application |
9.3.1.5.US NLP in Healthcare & Life Sciences Market, by End Use |
9.3.2.Canada |
9.3.3.Mexico |
*Similar segmentation will be provided at each and country level |
9.4.Europe |
9.5.APAC |
9.6.Latin America |
9.7.Middle East & Africa |
10.Competitive Landscape |
10.1.Overview of the Key Players |
10.2.Competitive Ecosystem |
10.2.1.Platform Manufacturers |
10.2.2.Subsystem Manufacturers |
10.2.3.Service Providers |
10.2.4.Software Providers |
10.3.Company Share Analysis |
10.4.Company Benchmarking Matrix |
10.4.1.Strategic Overview |
10.4.2.Product Innovations |
10.5.Start-up Ecosystem |
10.6.Strategic Competitive Insights/ Customer Imperatives |
10.7.ESG Matrix/ Sustainability Matrix |
10.8.Manufacturing Network |
10.10.1.Locations |
10.10.2.Supply Chain and Logistics |
10.10.3.Product Flexibility/Customization |
10.10.4.Digital Transformation and Connectivity |
10.10.5.Environmental and Regulatory Compliance |
10.9.Technology Readiness Level Matrix |
10.10.Technology Maturity Curve |
10.11.Buying Criteria |
11.Company Profiles |
11.1.Alphabet, Inc. |
11.1.1.Company Overview |
11.1.2.Company Financials |
11.1.3.Product/Service Portfolio |
11.1.4.Recent Developments |
11.1.5.IMR Analysis |
*Similar information will be provided for other companies |
11.2.IBM |
11.3.Microsoft |
11.4.IQVIA |
11.5.AWS |
11.6.AVERBIS |
11.7.SAS Institute |
11.8.3M |
11.9.Dassault Systèmes |
11.10.Oracle |
12.Appendix |
A comprehensive market research approach was employed to gather and analyze data on the NLP in Healthcare & Life Sciences Market. In the process, the analysis was also done to estimate the parent market and relevant adjacencies to measure the impact of them on the NLP in healthcare & life sciences market. The research methodology encompassed both secondary and primary research techniques, ensuring the accuracy and credibility of the findings.
Secondary research involved a thorough review of pertinent industry reports, journals, articles, and publications. Additionally, annual reports, press releases, and investor presentations of industry players were scrutinized to gain insights into their market positioning and strategies.
Primary research involved conducting in-depth interviews with industry experts, stakeholders, and market participants across the NLP in healthcare & life sciences ecosystem. The primary research objectives included:
A combination of top-down and bottom-up approaches was utilized to estimate the overall size of the NLP in healthcare & life sciences market. These methods were also employed to estimate the size of various subsegments within the market. The market size estimation methodology encompassed the following steps:
To ensure the accuracy and reliability of the market size estimates, data triangulation was implemented. This involved cross-referencing data from various sources, including demand and supply side factors, market trends, and expert opinions. Additionally, top-down and bottom-up approaches were employed to validate the market size estimates.