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Natural Language Processing (NLP) in Healthcare Market - Global Growth, Trends and Forecast (2022- 2027) By Types, By Application, By Regions and By Key Players: 3M, Linguamatics, Amazon AWS

29 Mar, 2022 | 161 Pages
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Natural Language Processing (NLP) in Healthcare Market was valued at USD 582.7 million in 2020 and is expected to reach USD 2128.3 million by 2028, growing at a CAGR of 20.3% from 2022 to 2028.



Natural Language Processing (NLP) in Healthcare Market Overview



The main growth factors of the NLP in the healthcare and life sciences market contain the rising demand for improving Electronic Health Records (EHRs) data usability to improve patient care, and the ability to analyze and extract meaning from narrative texts and non-related data sources.



Presently, the implementation of the NLP technology is rising in the global healthcare industry. Some public, as well as private healthcare service providers such as clinics and notable hospitals, are adopting NLP technology for clinical applications to improve their patient engagement and overall decision-making capabilities. In addition to this, the NLP technology is primarily applied as a tactical tool by these healthcare service providers to increase clinical data insights and real data results after clinical processes. The NLP technology is mainly used in artificial intelligence systems to get improved data insights. These applications with the natural language processing integration are used in the healthcare industry for clinical decision support systems and predictive analysis. NLP may also enhance the customer experience programs with various added benefits, thereby attracting more consumers, which, in turn, is projected to have a positive impact on the market growth in the country. The increasing innovations in the market studied, by the global players based in the United States, are bringing development into the NLP market and fueling the rate of product launch in the region.



Who are the Major Players in Natural Language Processing (NLP) in Healthcare Market?



Natural Language Processing (NLP) in Healthcare Market is rising at a very fast pace and has seen the focus of many local and regional vendors offering precise application products for numerous end users. The three dependencies for the status of major companies in the market are: company profile, profitable gross margin, the prices they charge. These are the main players in this market includes 3M, Linguamatics, Amazon AWS, Nuance Communications, SAS, IBM, Microsoft Corporation, Averbis, Health Fidelity, Dolbey Systems, Melax Tech



Recent Developments



Baidu Inc. presented Ernie-M, which is a multilingual model that could analyze 96 languages. It is a training model and has the capacity to improve the cross-lingual transferability on languages that are data-sparse.



Melax Tech Announces Launch of Mercury NLP, AI Technology To Improve Healthcare Research through Text Extraction & Normalization- Houston-based natural language processing (NLP) technology provider expands product line to aid healthcare and pharmaceutical industries in extracting critical information from medical texts



What are the major Applications, Types and Regions for Natural Language Processing (NLP) in Healthcare Market?



Natural Language Processing (NLP) in Healthcare Market is segmented based on the type, applications, companies and regions.



By Type, it is segmented into




  • Machine Translation

  • Information Extraction

  • Automatic Summarization

  • Text and Voice Processing

  • Other

  • By type, machine translation is the most commonly used type, with about 44% market share in 2018.



By Applications, it is segmented into




  • Electronic Health Records (EHR)

  • Computer-Assisted Coding (CAC)

  • Clinician Document

  • Other

  • By application, EHR is the largest segment, with a market share of about 48% in 2018, while CAC segment was expected to increase at nearly EHR by 2025.



Natural Language Processing (NLP) in Healthcare Market Regional Analysis



All these factors greatly affect the Natural Language Processing (NLP) in the Healthcare market growth. It further aims at offering a complete overview on a detailed assessment of important features of different industries including sales volume, market revenue, and demand size, sales growth, pricing analysis and changing market growth factors in regions such as Follows,




  • North America


    • US

    • Canada



  • Europe

    • Germany

    • France

    • UK

    • Italy

    • Spain

    • Rest of Europe



  • Asia-Pacific

    • China

    • Japan

    • India

    • Australia

    • South Korea

    • Rest of Asia-Pacific



  • Rest of the World

    • Middle East & Africa

    • Latin America





The Natural Language Processing (NLP) in Healthcare Market describes the factors driving the global growth opportunities in upcoming years and highlights market channels. In addition, the report analyzes market size and share, trends, by geographic region, end-use type, and segment. It focuses extensively on revealing a detailed regional analysis. The Global Natural Language Processing (NLP) in Healthcare Market report also conducted a PESTEL analysis of the industry to study the main influencing factors and entry barriers of the industry.



What is our Natural Language Processing (NLP) in Healthcare Market report scope?



Scope of the Report covers Natural Language Processing (NLP) in Healthcare Market with a detailed analysis of the overall scenario for the market. It also highlights the business participants' environment in the global marketplace. This report also provides an overview of leading companies covering the latest successful marketing strategies, market contributions, current and historical background and latest market happenings to help key organizations to grow and generate larger profits. Business players will greatly benefit from this Natural Language Processing (NLP) in Healthcare Market analysis report as it has vital details to provide about regional markets, expected opportunities for the prediction time period 2022-2027. Growth between segments is used to understand the different growth factors that are expected to dominate the market as a whole and to develop strategies to differentiate between key applications and target markets. It further reveals how worldwide market is working through efficient information graphics.



Key Takeaways from this Natural Language Processing (NLP) in Healthcare Report




  • Evaluate Natural Language Processing (NLP) in Healthcare market potential through analyzing growth rates (CAGR %), Volume (Units) and Value ($M) data given at country level - for product types, end use applications and by different industry verticals.

  • Understand the different dynamics influencing the market - growth driving factors, specific challenges and hidden opportunities.

  • Get in-depth insights on your competitor performance – revenue, shares, business strategies, financial benchmarking, product benchmarking, SWOT analysis and more.

  • Analyze the sales and distribution channels across geographies to enhance top-line revenues.

  • Understand the demanding supply chain with a deep dive on the value augmentation at each, in order to optimize value and bring efficiencies in your processes.

  • Get a quick outlook on the Natural Language Processing (NLP) in Healthcare market entropy - M&A's, deals, partnerships, product launches of all key players for the past 4 years.

  • Evaluate the import-export statistics, supply-demand and competitive landscape for more than top 20 countries globally for the market.



All our reports are custom made to your company needs to a certain extent, we do provide 5 free consulting hours along with purchase of each report, and this will allow you to request any additional data to customize the report as your needs.


  1. INTRODUCTION

    1. MARKET DEFINATION

    2. MARKET DYNAMICS

    3. MARKET SEGMENTATION

    4. REPORT TIMLINES

    5. KEY STAKEHOLDERS



  2. RESEARCH METHODOLOGY

    1. DATA MINING

      1. SECONDARY RESEARCH

      2. PRIMARY RESEARCH

      3. SUBJECT MATTER EXPERT ADVICE



    2. QUALITY CHECK

    3. FINAL REVIEW

      1. DATA TRIANGULATION

      2. BOTTOM-UP APPROACH

      3. TOP-DOWN APPROACH



    4. RESEARCH FLOW



  3. EXECUTIVE SUMMARY

    1. INTRODUCTION

    2. GLOBAL NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE MARKET BY APPLICATIONS

    3. GLOBAL NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE MARKET BY TYPES



  4. MARKET DYNAMICS

    1. DRIVERS

      1. INCREASING DEMAND FOR NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE



    2. RESTRAINTS

      1. STRINGENT ENVIRONMENTAL REGUALTIONS

      2. HIGH COST ON MATERIALS



    3. OPPORTUNITIES

      1. NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE GROWTH

      2. APPLICATION OF NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE



    4. IMPACT OF COVID 19



  5. GLOBAL NATURAL LANGUAGE PROCESSING (NLP) IN THE HEALTHCARE MARKET, BY TYPES

    1. Machine Translation

    2. Information Extraction

    3. Automatic Summarization

    4. Text and Voice Processing

    5. Other



  6. GLOBAL NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE MARKET, BY APPLICATION

    1. Electronic Health Records (EHR)

    2. Computer-Assisted Coding (CAC)

    3. Clinician Document

    4. Other



  7. GLOBAL NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE MARKET, BY REGION

    1. NORTH AMERICA

      1. US

      2. CANADA

      3. MEXICO



    2. EUROPE

      1. GERMANY

      2. FRANCE

      3. UK

      4. ITALY

      5. RUSSIA

      6. REST OF EUROPE



    3. APAC

      1. CHINA

      2. SOUTH KOREA

      3. JAPAN

      4. INDIA

      5. AUSTRALIA

      6. ASEAN

      7. REST OF APAC



    4. MIDDLE EAST & AFRICA

      1. SAUDI ARABIA

      2. UAE

      3. SOUTH AFRICA

      4. TURKEY

      5. REST OF MEA



    5. SOUTH AMERICA

      1. BRAZIL

      2. REST OF MEA

      3. ARGENTINA

      4. REST OF SOUTH AMERICA





  8. COMPETITIVE LANDSCAPE

    1. MERGERS, ACQUISITIONS, JOINT VENTURES, COLLABORATIONS,

    2. AND AGREEMENTS

      1. KEY DEVELOPMENT



    3. MARKET SHARE (%) **/RANKING ANALYSIS

    4. STRATEGIES ADOPTED BY LEADING PLAYERS



  9. COMPANY PROFILES

    1. BUSINESS OVERVIEW

    2. COMPANY SNAPSHOT

    3. PRODUCT BENCHMARKING

    4. STRATEGIC INITIATIVES

      1. 3M

      2. Linguamatics

      3. Amazon AWS

      4. Nuance Communications

      5. SAS

      6. IBM

      7. Microsoft Corporation

      8. Averbis

      9. Health Fidelity

      10. Dolbey Systems

      11. Melax Tech





SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.

PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.

MARKET ENGINEERING
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.

EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.

REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.

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