Natural Language Processing Market Size Analysis: Insights And Forecast To 2030
The Research Report on Natural Language Processing Market [117 Pages] offers thorough perspective on industry performance, latest key trends and comprehensive exploration of Industry segments by Type [Statistical NLP, Hybrid based NLP, Rule NLP], Applications [Machine translation, Information extraction, Report generation, Question answering, Others] and Regions. The report presents concise aspects on key dynamics with market growth rate, size, trade, and insights into key players. It highlights the convergence of market trends, business tactics, and the competitive environment. This report goes beyond conventional analyses by providing both qualitative and quantitative perspectives through SWOT and PESTLE evaluations. Through meticulous research and thorough analysis, the report aims to offer valuable insights to stakeholders, vendors, and various participants within the industry.
In our latest research report, we highlight the rapid growth of the global Natural Language Processing market and provide detailed insights into the projected market size, share, and revenue estimations up to 2030.Ask for Sample Report
Who is the Largest Player of Natural Language Processing Market worldwide?
Microsoft Corporation Salesforce.Com Inc. Inbenta Technologies Inc. AppOrchid Inc. SAS Institute Inc. Adobe Systems Incorporated Klevu Oy Nvidia Corporation Intel Corporation Verint System Inc. NetBase Solutions Inc. SAP SE Genpact Limited IBM Corporation Rasa Technologies GmbH Micro Focus International PLC (HPE) Amazon Web Services Inc. Veritone Inc. 3M Company Babylon Healthcare Services Limited Google Inc.
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What is Market Insights and Analysis?
The global Natural Language Processing market size was valued at USD 13017.98 million in 2022 and is expected to expand at a CAGR of 18.27% during the forecast period, reaching USD 35630.81 million by 2028.
The competitive landscape analysis encompasses a thorough examination of key players operating in the market. It assesses their market presence, product offerings, strategic initiatives, and growth trajectories. This analysis empowers businesses with valuable insights to make informed decisions, adapt to market trends, and devise effective strategies to maintain a competitive edge in the dynamic industry landscape.
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What are the factors driving the growth of the Natural Language Processing Market?
Growing demand for below applications around the world has had a direct impact on the growth of the Natural Language Processing
Machine translation
Information extraction
Report generation
Question answering
Others
What are the types of Natural Language Processing available in the Market?
Based on Product Types the Market is categorized into Below types that held the largest Natural Language Processing market share In 2023.
Statistical NLP
Hybrid based NLP
Rule NLP
Regional Outlook:
North America (United States, Canada and Mexico)
Europe (Germany, UK, France, Italy, Russia and Turkey etc.)
Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam)
South America (Brazil, Argentina, Columbia etc.)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)
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Following Key Questions Covered in this Report:
What is the Current Market Size and Growth Rate of the Natural Language Processing Market?
What are the Key Trends and Developments Shaping the Natural Language Processing Market?
What are the Main Drivers and Restraints Affecting the Growth of the Natural Language Processing Market?
How is the Natural Language Processing Market Segmented by Manufacturers, Types, Applications, and Regions?
Who are the Major Players in the Natural Language Processing Market and What are Their Strategies?
What is the Competitive Landscape and Market Share of Different Companies?
What are the Future Growth Prospects and Opportunities in the Natural Language Processing Market?
What are the Industry Challenges and Potential Mitigation Strategies?
How is Consumer Behavior Impacting Demand Patterns in the Natural Language Processing Market?
What is the Impact of Regulatory Policies on the Natural Language Processing Market?
What are the Technological Innovations and Advancements in the Natural Language Processing Industry?
What is the Forecasted Market Growth Rate and Potential Size in the Coming Years?
What are the Key Market Entry Barriers and How Can They Be Overcome?
What is the Impact of External Factors, such as COVID-19, on the Natural Language Processing Market?
What are the Evolving Customer Preferences and Their Impact on the Market?
Covid-19 Impact on Natural Language Processing Market:
The unprecedented outbreak of the Covid-19 pandemic has reverberated across industries worldwide, ushering in a period of profound transformation. The landscape of businesses and markets has been reshaped as supply chains were disrupted, consumer behaviors shifted, and economies faced unforeseen challenges. Comprehensive research on the Covid-19 impact on various industries has become imperative to understand the extent of its influence, ranging from disruptions in production and distribution to changes in demand patterns and workforce dynamics. This research delves into the multifaceted repercussions, offering insights into strategies for resilience, adaptation, and recovery. It sheds light on the evolving paradigms within industries, providing a roadmap for stakeholders to navigate these uncertain times with informed decisions and strategic responses.
Key inclusions of the Natural Language Processing market report:
A detailed impact analysis of COVID-19 on the Natural Language Processing market.
In-depth statistical analysis of market size, sales volume, and revenue, segmented by product type, application, and geography.
Comprehensive coverage of major market trends, including drivers, challenges, and opportunities.
Identification and analysis of growth opportunities for businesses operating in the Natural Language Processing market.
Accurate and up-to-date figures showcasing the market growth rate and projected growth trends.
A thorough examination of the advantages and disadvantages of both direct and indirect sales channels in the Natural Language Processing market.
Insights into the key players in the industry, including traders, distributors, and dealers, and their impact on the market.
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Detailed TOC of Natural Language Processing Market Research Report:
1 Natural Language Processing Market Overview
1.1 Product Overview and Scope of Natural Language Processing Market
1.2 Natural Language Processing Market Segment by Type
1.3 Global Natural Language Processing Market Segment by Application
1.4 Global Natural Language Processing Market, Region Wise (2017-2029)
1.5 Global Market Size (Revenue) of Natural Language Processing (2017-2029)
1.5.1 Global Natural Language Processing Market Revenue Status and Outlook (2017-2029)
1.5.2 Global Natural Language Processing Market Sales Status and Outlook (2017-2029)
1.6 Influence of Regional Conflicts on the Natural Language Processing Industry
1.7 Impact of Carbon Neutrality on the Natural Language Processing Industry
2 Natural Language Processing Market Upstream and Downstream Analysis
2.1 Natural Language Processing Industrial Chain Analysis
2.2 Key Raw Materials Suppliers and Price Analysis
2.3 Key Raw Materials Supply and Demand Analysis
2.4 Market Concentration Rate of Raw Materials
2.5 Manufacturing Process Analysis
2.6 Manufacturing Cost Structure Analysis
2.6.1 Labor Cost Analysis
2.6.2 Energy Costs Analysis
2.6.3 RandD Costs Analysis
2.7 Major Downstream Buyers of Natural Language Processing Analysis
2.8 Impact of COVID-19 on the Industry Upstream and Downstream
3 Players Profiles
4 Global Natural Language Processing Market Landscape by Player
4.1 Global Natural Language Processing Sales and Share by Player (2017-2022)
4.2 Global Natural Language Processing Revenue and Market Share by Player (2017-2022)
4.3 Global Natural Language Processing Average Price by Player (2017-2022)
4.4 Global Natural Language Processing Gross Margin by Player (2017-2022)
4.5 Natural Language Processing Market Competitive Situation and Trends
4.5.1 Natural Language Processing Market Concentration Rate
4.5.2 Natural Language Processing Market Share of Top 3 and Top 6 Players
4.5.3 Mergers and Acquisitions, Expansion
5 Global Natural Language Processing Sales, Revenue, Price Trend by Type
5.1 Global Natural Language Processing Sales and Market Share by Type (2017-2022)
5.2 Global Natural Language Processing Revenue and Market Share by Type (2017-2022)
5.3 Global Natural Language Processing Price by Type (2017-2022)
5.4 Global Natural Language Processing Sales, Revenue and Growth Rate by Type (2017-2022)
6 Global Natural Language Processing Market Analysis by Application
6.1 Global Natural Language Processing Consumption and Market Share by Application (2017-2022)
6.2 Global Natural Language Processing Consumption Revenue and Market Share by Application (2017-2022)
6.3 Global Natural Language Processing Consumption and Growth Rate by Application (2017-2022)
7 Global Natural Language Processing Sales and Revenue Region Wise (2017-2022)
7.1 Global Natural Language Processing Sales and Market Share, Region Wise (2017-2022)
7.2 Global Natural Language Processing Revenue and Market Share, Region Wise (2017-2022)
7.3 Global Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.4 United States Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.5 Europe Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.6 China Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.7 Japan Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.8 India Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.9 Southeast Asia Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.10 Latin America Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
7.11 Middle East and Africa Natural Language Processing Sales, Revenue, Price and Gross Margin (2017-2022)
8 Global Natural Language Processing Market Forecast (2022-2029)
8.1 Global Natural Language Processing Sales, Revenue Forecast (2022-2029)
8.2 Global Natural Language Processing Sales and Revenue Forecast, Region Wise (2022-2029)
8.3 Global Natural Language Processing Sales, Revenue and Price Forecast by Type (2022-2029)
8.4 Global Natural Language Processing Consumption Forecast by Application (2022-2029)
8.5 Natural Language Processing Market Forecast Under COVID-19
9 Industry Outlook
9.1 Natural Language Processing Market Drivers Analysis
9.2 Natural Language Processing Market Restraints and Challenges
9.3 Natural Language Processing Market Opportunities Analysis
9.4 Emerging Market Trends
9.5 Natural Language Processing Industry Technology Status and Trends
9.6 News of Product Release
9.7 Consumer Preference Analysis
9.8 Natural Language Processing Industry Development Trends under COVID-19 Outbreak
10 Research Findings and Conclusion
11 Appendix
11.1 Methodology
11.2 Research Data Source
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Natural Language Processing (NLP) Market Outlook 2023-2030: Latest Trends, Opportunities, And Future Growth Predictions
The "Natural Language Processing (NLP) Market" Research Report 2023: incorporates a thorough qualitative and quantitative analysis along with several market dynamics. Global Natural Language Processing (NLP) Market size was valued at USD 703 million in 2022, and poised to rise at an impressive growth rate of USD 2529.8 million by 2027 as projected. The report anticipates a robust growth trajectory, demonstrated by an impressive (Compound Annual Growth Rate) CAGR of 20.1% during the forecast 2023-2028. This research provides a roadmap of the Natural Language Processing (NLP) industry by including details on significant growth factors, future developments, important business tactics, and top company opportunities. It also contains historical data, future product environments, marketing plans, and technology advancements.
According to the Newest 108 Pages Report contains market size, share, key company analysis, profit and deals, exclusive data, vital statistics, current advancements, and competitive landscape details. Ask for Sample Report
Who Are the Leading Key Players Operating in This Market?The report offers a detailed analysis supported by reliable statistics on sales and revenue by players for the period 2018-2023. Company profiles and market share analyses of the prominent players are also provided in this section.
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Attractive Natural Language Processing (NLP) Market Opportunities and Insights: -The report offers key success strategies for leading companies, Key market dynamics including trends, drivers, challenges, and opportunities. Further, critical Natural Language Processing (NLP) market strategies, Porter's five forces, market attractiveness, and growth-share matrix are covered.
The Global Natural Language Processing (NLP) market is anticipated to rise at a considerable rate during the forecast period, between 2023 and 2030. In 2023, the market is growing at a steady rate, and with the rising adoption of strategies by key players, the market is expected to rise over the projected horizon.
Natural language processing (NLP) is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language (spoken or written data), not in the artificial languages such as Java and C++.
Global Natural Language Processing (NLP) key players include 3M, Linguamatics, Amazon AWS, etc. Global top three manufacturers hold a share about 35Percent.
United States is the largest market, with a share about 65Percent, followed by Europe and China, both have a share about 25 percent.
In terms of product, Machine Translation is the largest segment, with a share about 45Percent. And in terms of application, the largest application is Electronic Health Records (EHR), followed by Computer-Assisted Coding (CAC).
Market Analysis and Insights: Global Natural Language Processing (NLP) Market The global Natural Language Processing (NLP) market size is projected to reach USD 2529.8 million by 2027, from USD 703 million in 2020, at a CAGR of 20.1% during 2021-2027.
With industry-standard accuracy in analysis and high data integrity, the report makes a brilliant attempt to unveil key opportunities available in the global Natural Language Processing (NLP) market to help players in achieving a strong market position. Buyers of the report can access verified and reliable market forecasts, including those for the overall size of the global Natural Language Processing (NLP) market in terms of revenue.
On the whole, the report proves to be an effective tool that players can use to gain a competitive edge over their competitors and ensure lasting success in the global Natural Language Processing (NLP) market. All of the findings, data, and information provided in the report are validated and revalidated with the help of trustworthy sources. The analysts who have authored the report took a unique and industry-best research and analysis approach for an in-depth study of the global Natural Language Processing (NLP) market.
Global Natural Language Processing (NLP) Scope and Market Size Natural Language Processing (NLP) market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Natural Language Processing (NLP) market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2016-2027.
TO KNOW HOW COVID-19 PANDEMIC AND RUSSIA UKRAINE WAR WILL IMPACT THIS MARKET - REQUEST A SAMPLE Market Segments Analysis:This report has explored the key segments: by Type and by Application. This report also provides sales, revenue, and average price forecast data by type and by application segments based on production, price, and value for the period 2017-2028.
On the basis of Product Type, this report displays the production, revenue, price, market share, and growth rate of each type, primarily split into:
On the basis of the End Users/Applications, this report focuses on the status and outlook for major applications/end users, consumption (sales), market share, and growth rate for each application, including:
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
Which region is dominating the Natural Language Processing (NLP) market growth?
Natural Language Processing (NLP) Market- New Research Highlights
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Natural Language Processing (NLP) Market Latest Trends:The market research industry is in a state of rapid evolution, adapting to the ever-changing business environment and leveraging the latest trends and technological tools. The report often sheds light on new methodologies, and technological advancements and offers insights to align research processes. Recent trends underscore the importance of digital transformation, with an emphasis on artificial intelligence and data analytics to decipher complex consumer patterns.
Natural Language Processing (NLP) Market Driving Factors:The driving factors behind the growing Natural Language Processing (NLP) industry include the increasing competition in global markets, rapid technological advancements, and evolving consumer preferences. Businesses are recognizing the imperative need for data-driven decision-making to gain a competitive edge. Additionally, the rise of digital platforms and social media has provided a goldmine of consumer insights, further propelling the demand for comprehensive market research.
Some of the Key Questions Answered in the Natural Language Processing (NLP) Market Report:
Detailed TOC of Global Natural Language Processing (NLP) Industry Research Report, Growth Trends and Competitive Analysis 2023-2030
1 Report Overview1.1 Study Scope 1.2 Market Analysis by Type 1.2.1 Global Natural Language Processing (NLP) Market Size Growth Rate by Type: 2017 VS 2021 VS 2028 1.3 Market by Application 1.3.1 Global Natural Language Processing (NLP) Market Growth Rate by Application: 2017 VS 2021 VS 2028 1.4 Study Objectives 1.5 Years Considered
2 Market Perspective2.1 Global Natural Language Processing (NLP) Market Size (2017-2028) 2.2 Natural Language Processing (NLP) Market Size across Key Geographies Worldwide: 2017 VS 2021 VS 2028 2.3 Global Natural Language Processing (NLP) Market Size by Region (2017-2022) 2.4 Global Natural Language Processing (NLP) Market Size Forecast by Region (2023-2028) 2.5 Global Top Natural Language Processing (NLP) Countries Ranking by Market Size
3 Natural Language Processing (NLP) Competitive by Company3.1 Global Natural Language Processing (NLP) Revenue by Players 3.1.1 Global Natural Language Processing (NLP) Revenue by Players (2017-2022) 3.1.2 Global Natural Language Processing (NLP) Market Share by Players (2017-2022) 3.2 Global Natural Language Processing (NLP) Market Share by Company Type (Tier 1, Tier 2, and Tier 3) 3.3 Company Covered: Ranking by Natural Language Processing (NLP) Revenue 3.4 Global Natural Language Processing (NLP) Market Concentration Ratio 3.4.1 Global Natural Language Processing (NLP) Market Concentration Ratio (CR5 and HHI) 3.4.2 Global Top 10 and Top 5 Companies by Natural Language Processing (NLP) Revenue in 2021 3.5 Global Natural Language Processing (NLP) Key Players Head office and Area Served 3.6 Key Players Natural Language Processing (NLP) Product Solution and Service 3.7 Date of Enter into Natural Language Processing (NLP) Market 3.8 Mergers and Acquisitions, Expansion Plans
4 Global Natural Language Processing (NLP) Breakdown Data by Type4.1 Global Natural Language Processing (NLP) Historic Revenue by Type (2017-2022) 4.2 Global Natural Language Processing (NLP) Forecasted Revenue by Type (2023-2028)
5 Global Natural Language Processing (NLP) Breakdown Data by Application5.1 Global Natural Language Processing (NLP) Historic Market Size by Application (2017-2022) 5.2 Global Natural Language Processing (NLP) Forecasted Market Size by Application (2023-2028)
6 North America6.1 North America Natural Language Processing (NLP) Revenue by Company (2020-2022) 6.2 North America Natural Language Processing (NLP) Revenue by Type (2017-2028) 6.3 North America Natural Language Processing (NLP) Revenue by Application (2017-2028) 6.4 North America Natural Language Processing (NLP) Revenue by Country (2017-2028) 6.4.1 U.S. 6.4.2 Canada
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Natural Language Processing To Extract Social Risk Factors Influencing Health
Social risk factors such as financial instability and housing insecurity are increasingly recognized as influencing health. But unlike diagnosis codes, prescription information, lab or other test reports, social risk factors do not adhere to standardized, controlled terminology in a patient's electronic medical record, making this information difficult to extract from the clinical notes where they typically are found.
A new study has found that a natural language processing (NLP) system developed by Regenstrief Institute and Indiana University Richard M. Fairbanks School of Public Health informaticians showed excellent performance when ported to a new health system and tested on more than six million clinical notes of patients seen in Florida. Performance was evaluated for generalizability and portability, defined as ease and accuracy when deploying the software in a new environment and of updating its use to meet the needs of new data.
"Social factors have a great impact on our health. It's not just the medical care that we receive, but it's also the places where we live, the places where we work and our access to food and transportation and other resources that have a major influence on our health," said Chris Harle, Ph.D., the Regenstrief and IU Fairbanks School faculty member who is senior author on the study.
"It's important for the clinicians and health systems providing medical care to know about people's social risk factors so when prescribing medications, ordering tests or planning to perform a procedure, they can better treat the whole person—perhaps with lower cost drugs or alternative sources for tests—and can also link them to services that help address their needs for a safe place to live and healthy food to eat."
In this study, the researchers' NLP rule-based model searched through text that physicians or other clinicians had written in the clinical notes of patients' electronic health records, looking for key words or phrases that were likely to indicate difficulty with housing (for example: lack of permanent address) or financial needs (for example: inability to afford follow-up care) of patients at a health care system in a new and quite different geographic area.
In spite of challenges (for example: name of a homeless shelter without indication of the facility's function or regional variation or local nuances in language), the research scientists verified that the NLP models, with relatively simple modifications, could deliver highly accurate performance as compared to the gold standard of human review.
"Is a patient diagnosed with diabetes? It's relatively easy to find that information in an electronic health record because the same words and codes are more likely to be used in health systems in central Indiana as are used in Florida or elsewhere in the U.S. But social risk factors don't have nearly as established and widely used words, phrases or codes to identify them. Therefore, it's harder to search through and determine a patient has a financial need than it is to say a patient has diabetes," said Dr. Harle.
"Our work is important for patients because ultimately their health is related to a variety of factors in their life, including social factors. For example, are clinicians incorporating in their decision making a patient's ability to recover from a surgery as it's going to be different if they have stable housing versus unstable housing?"
"The more that we can disseminate and adapt natural language processing and other artificial intelligence methods that fully describe a patient to give clinicians a full 360 understanding of patients' needs, the better. If we can extract social information more efficiently, it's less costly. Then we can start to take what we'd call a population health perspective."
"So, if a health system can efficiently identify the patients who have housing instability—the population of patients who have this need—then the health care system may be able to employ a more proactive population-based intervention to serve that whole group of people, connecting them, for example, to the housing services in the community or financial resources that might be available."
Dr. Harle, an information scientist and health services researcher who focuses on the design, adoption, use and value of health information systems, notes that this study was a team effort across multiple institutions of professionals who work in the clinical arena (including individuals who study how patients access and use care), public health, population health and health care administration as well as technically knowledgeable and skilled systems specialists.
"Bringing people together who have that diversity of understanding leads to pragmatically useful studies like this one," he said.
"Generalizability and portability of natural language processing system to extract individual social risk factors" is published in the International Journal of Medical Informatics.
More information: Tanja Magoc et al, Generalizability and portability of natural language processing system to extract individual social risk factors, International Journal of Medical Informatics (2023). DOI: 10.1016/j.Ijmedinf.2023.105115
Citation: Natural language processing to extract social risk factors influencing health (2023, August 21) retrieved 6 September 2023 from https://medicalxpress.Com/news/2023-08-natural-language-social-factors-health.Html
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