Global Healthcare Natural Language Processing Market – Overview

Natural language processing or NLP generally refers to the interaction between human and computer that analyzes, processes, and produces computational linguistics all based on a human language. The NLP technology helps humans to have a meaningful interaction with computers using basic human language such as German or English instead of artificial computer languages such as C++ or Java. Currently, the implementation of the NLP technology is growing in the global healthcare industry. Several 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 implemented as a tactical tool by these healthcare service providers to gain clinical data insights and effective data results after clinical processes. The NLP technology is mainly used in the 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 system and predictive analysis. Similarly, numerous companies are now implementing deep learning or machine learning applications with the aid of the natural language processing technology to gain knowledge from several clinical documents.

As per the research report by Transparency Market Research about the global healthcare natural language processing market is expected to be on course to reach a hefty valuation worth US$7,450.8 mn by the year 2027. This growth of the global market is expected to be achieved with the help of a massive CAGR of 19.1% over the course of the given forecast period of 2019 to 2027. Of the different regional segment of the global market, North America is projected to head the lot in terms of value, which will then be followed by the regional segment of Europe.

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global healthcare natural language processing market

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Growing EHR Adoption to Drive Market Development

The healthcare natural language processing market is mainly driven by the considerable rise in terms of volume of the unorganized clinical information. Growing adoption of the EHR (electronics health records) systems in the global healthcare industry is leading to creation of vast amounts of clinical data that comprises of patient details and their diagnosis procedures along with other relevant information such as the details of their medication. In addition to this, the integration of NLP technology with computer apps helps these healthcare service providers to improve patient and their family engagement experience. It also helps them in cutting down the operational costs by removing the need for paper-based clinical documentation procedures.

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North America to Continue Leading Market in Coming Years

In terms of geographical segmentation, there are five major regions of the global healthcare natural language processing language market. These regions are Latin America, Europe, Asia Pacific, Middle East and Africa, and North America. Of these, currently, the global market is being dominated by the regional segment of North America. The market in North America receives the benefits of getting newer technologies early and experimenting with them. Moreover, being home to several notable players operating in the healthcare natural language processing market, the region enjoys superior growth rate as compared to the other regional market. In addition to this, presence of a matured and highly developed healthcare infrastructure also helps in the further bolstering of the market scope.

Some of the key companies operating in the global healthcare natural language processing market are NLP Technologies Inc., NEC Corporation, Apple Inc., Microsoft Corporation, Dolbey Systems Inc., IBM Corporation, NetBase Solutions Inc., SAS Institute Inc., Microsoft Corporation, Verint Systems Inc., eContext, Artificial Solutions, and Linguamatics Ltd. among others.

The report offers intricate dynamics about the different aspects of the healthcare natural language processing (NLP) market that aids companies operating in the market in making strategic development decisions. TMR’s study also elaborates on the significant changes that are highly anticipated to boost the healthcare natural language processing (NLP) market during the forecast period. It also includes a key indicator assessment to highlight the growth prospects of the healthcare natural language processing (NLP) market, and estimate statistics related to the market progress in terms of value (US$ Mn).  

This report provides an analysis of the global healthcare natural language processing (NLP) market for the period from 2017 to 2027, wherein the period from 2019 to 2027 comprises the forecast period and 2018 is the base year. Data for 2017 is provided as historical information. The report details the prominent trends and technologies playing a major role in the growth of the Healthcare Natural Language Processing (NLP) market over the forecast period. It also highlights various drivers, restraints, and opportunities expected to influence the market’s growth during this period. The study provides a holistic perspective of the expansion of the Healthcare Natural Language Processing (NLP) market during the forecast period in terms of revenue estimates (in US$ Mn), across Asia Pacific (APAC), South America, North America, Europe, and Middle East & Africa (MEA) regions. The report provides analysis of the global Healthcare Natural Language Processing (NLP) market in terms of market estimates and forecasts for all the segments across different geographic regions.

Increasing penetration of electronics health record (EHR) systems in healthcare applications is significantly fueling the demand for knowledge extraction and structured information. Additionally, the Healthcare Natural Language Processing (NLP) market is mainly driven by exponential rise in volume of unstructured clinical data. The NLP technology enables health professionals to enhance the overall performance of clinical process by attaining clinical communication techniques. NLP technology based systems also allow organizations to improve family and patient engagement, and assist in reduction of operational cost by elimination of traditional clinical documentation process. Furthermore, increasing spending on healthcare IT expenditure across European countries in order to implement advance technologies in clinical diagnosis procedures. Healthcare organizations are implementing NLP technologies for clinical documentation purpose in order to reduce incidental errors, financial losses, and attain high quality patient care and better patient outcomes. The report includes the impact analysis of such factors under the market dynamics, categorized as the drivers and the restraints. Moreover, the report also details on different NLP techniques while providing holistic view of the market under the ecosystem analysis. In ecosystem analysis, the study elucidates the workflow of entire Healthcare Natural Language Processing (NLP) system from generation of unstructured data to the end-use healthcare systems.

The report provides extensive information on key developments of NLP system across the countries and opportunities for global Healthcare Natural Language Processing (NLP) market. This is in consideration to the growing implementation of machine translation and information extraction technology, which is anticipated to offer prominent opportunities for Healthcare Natural Language Processing (NLP) market across the world in near term. Furthermore, increasing integration of data and network technologies such as Big Data, and Internet of Things (IoT) has varying degree of acceptance across regions and in healthcare applications, which is further anticipated to positively influence the demand for NLP technology across worldwide during the forecast period.

Based on technology, the global Healthcare Natural Language Processing (NLP) market has been categorized into machine translation, information extraction, automatic summarization, and text and voice processing. The study includes global and regional key trends and key market indicators of the Healthcare Natural Language Processing (NLP) market. The report also includes detailed information of technology segment across each region for global Healthcare Natural Language Processing (NLP) market. Moreover, the report also includes competitive profiling of the regional and global key players associated with the Healthcare Natural Language Processing (NLP) market. The important business strategies adopted by them, their market positioning, and recent developments have also been identified in the research report.

Increase in developments in NLP technology across healthcare applications is leading toward high competition in the global Healthcare Natural Language Processing (NLP) market. Major players in the global Healthcare Natural Language Processing (NLP) market include NLP Technologies, Inc., NEC Corporation, Apple, Inc., Microsoft Corporation, Dolbey Systems, Inc., IBM Corporation, NetBase Solutions, Inc., SAS Institute, Inc., Verint Systems, Inc., eContext, Linguamatics Ltd., and Artificial Solutions.

Market Segmentation

Healthcare Natural Language Processing (NLP) Market, by Technology

  • Machine Translation
  • Information Extraction
  • Automatic Summarization
  • Text and Voice Processing

In addition, the report provides analysis of the Healthcare Natural Language Processing (NLP) market with respect to the following geography segments:

  • North America
    • U.S.
    • Canada
    • Rest of North America
  • Europe
    • The U.K.
    • Germany
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia Pacific (APAC)
    • China
    • Japan
    • India
    • Indonesia
    • Rest of APAC
  • Middle East & Africa (MEA)
    • Unite Arab Emirates (UAE)
    • Saudi Arabia
    • South Africa
    • Rest of MEA
  • South America
    • Brazil
    • Rest of South America

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Healthcare Natural Language Processing Market

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