Healthcare Natural Language Processing (NLP) Market: Good Growth Detected in the Near Future

Natural language processing (NLP) technologies allows humans to interact with computers through conventional languages such as English and German instead of artificial languages such as Java and C++. These technologies use a computer to process, analyze, and generate computational linguistics on the basis of human languages. Currently, NLP technology is being extensively used in the healthcare industry as several public and private health organizations are using it for clinical applications. Hospitals and clinics are adopting these technologies to improve patient engagement and bring in efficiency in decision-making capabilities. Owing to these reasons, the global healthcare natural language processing market is expected to be worth US$4.3 bn by the end of 2024 from US$936 mn in 2015. Between the years of 2016 and 2024, the global market is expected to expand at a CAGR of 18.8%.

The demand for NLP technology is expected to surge in the coming years as it is being used as a strategic tool to derive meaningful comprehensive of clinical informatics for effective outcomes by the healthcare industry. Used as a part of artificial intelligence systems, applications of NLP technologies are being deployed for predictive analysis and clinical decision support systems. The global healthcare natural language processing market is expected to receive an impetus from the uptake of these technologies by several companies for extracting knowledge from several clinic documents via machine learning or deep learning applications. The growing volume of unstructured clinical data and the unstoppable penetration of electronics health record (EHR) systems are expected to fuel the growth of this market in the coming years.

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On the basis of technology, healthcare NLP market is fragmented into machine translation, information extraction, automatic summarization, and text and voice processing. Out of these, the demand for machine translation and information extraction is expected to remain high in the healthcare applications in the coming years. The increasing influx of unstructured clinical information and pressing need for data analytics in clinical applications for text mining and document classification is expected to drive this demand. On the other hand, the text and voice processing segment is also projected to come across a plethora of opportunities in the healthcare NLP market. Factors such as growing adoption of speech recognition, and voice processing systems in EHR platforms, and artificial intelligence applications will boost the growth of the aforementioned segment.

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Geographically, the global healthcare natural language processing market is segmented into North America, Europe, Asia Pacific, South America, the Middle East and Africa, and Latin America. Presently, North America and Europe are leading the global market. The dominance of North America is attributable to the growing adoption of advanced technologies in healthcare applications and a strong foothold NLP technology providers. This regional market is also likely to thrive due to growing number healthcare organizations that are focusing on real-time analytics along with the integration of data analytics in various clinical processes. Furthermore, the growing investments by companies in developing improved NLP technology and artificial intelligence with the help of machine learning and automated decision-making support systems are also expected to drive the North America healthcare natural language processing market in the coming years.

The key players 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., Verint Systems, Inc., eContext, Linguamatics Ltd., and Artificial Solution. Several companies are making terrific investments in developing advanced technologies and diversified solutions for healthcare applications.

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