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<br>Read here the latest updates on the Natural language processing (nlp) in healthcare published by the CMI team.<br>
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NATURAL LANGUAGE PROCESSING (NLP) IN HEALTHCARE & LIFE SCIENCES MARKET ANALYSIS Natural Language Processing (NLP) in Healthcare and Life Sciences Market, by Component Type ((Technology (Interactive Voice Response, Pattern and Image Recognition, Text Analytics, and Speech Analytics) and Services)), by Application (Predictive Risk Analytics, Machine Translation, Information Extraction, and Report Generation), by Deployment Mode (On-premise and Cloud), and by Region (North America, Latin America, Europe, Asia Pacific, Middle East, and Africa) - Size, Share, Outlook, and Opportunity Analysis, 2018 - 2026
Integrating Natural Language Processing (NLP) platform helps both customer as well as service provider to easy the workflow. Voice assistants and messaging platforms used by consumers help in reducing time required for different services as patient documentation. NLP is the ability of a computer program to understand human languages and promotes human-machine interaction. Increasing adoption of digital technology in the healthcare industry and customer demand for better healthcare services is expected to drive growth of the market. The global natural language processing (NLP) in healthcare and life sciences market size was valued at US$ 1,497.89 million in 2018, and is expected to witness a CAGR of 26.8% over the forecast period (2019 – 2026).
Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market Share (%) Analysis, By Product Type, 2018 and 2026
Increasing data operations and use of smart devices is expected to drive growth of the Natural Language Processing (NLP) in healthcare and life sciences market Healthcare and life sciences industry generates large amount of data, which is driven by compliance & regulatory requirements, record keeping, and patient care. Growing trend of digitization and data driven solutions to improve healthcare delivery system is driving growth of the market. Therefore, increasing data-driven operations and decision-making is a major factor driving growth of the market. For instance, in May 2018, Google AI collaborated with University of California, San Francisco, Stanford Medicine, and The University of Chicago Medical Center to integrate Machine Learning in Electronic Health Records (EHR) in order to achieve scalable and accurate results and develop a data processing pipeline for transforming EHR files into a standardized format. Furthermore, several physicians prefer voice notes instead of handwritten or typed ones. Therefore, NLP platform can be used to easily interpret speech and update records accurately.
Natural Language Processing (NLP) in Healthcare and Life Sciences Market - Restraints NLP implementation is a major challenge in the healthcare and life sciences sector, which is expected to hamper the market growth over the forecast period. There are many countries in the world where healthcare facilities have a very little access for the general population along with lack of healthcare expenditure expected to hamper the NLP in healthcare and life sciences market. For instance, according to April 2017 World Health Organization’s (WHO) report, the ranking data reveals Malawi’s health system as number 185 out of 190 due to lack of manpower, lack of skills and scarcity of appropriate equipment and technology.
Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market Value (US$ Mn) & Y-o-Y Growth (%), 2016-2026
Natural Language Processing (NLP) in Healthcare and Life Sciences Market - Regional Insights On the basis of region, the global Natural Language Processing (NLP) in healthcare and life sciences market is segmented into North America, Latin America, Europe, Asia Pacific, Middle East, and Africa. North America is expected to hold dominant position in the global Natural Language Processing (NLP) in healthcare and life sciences market during the forecast period, owing to increasing demand for NLP platforms for data extraction and generation in clinical research in the healthcare and life sciences sector. For instance, in March 2017, Optra Systems announced the launch of its computational platform iMaven Knowledge Automation for clinical genomics using proprietary advanced NLP algorithms and Deep Machine Learning during the ACMG Clinical Genetics Annual Meeting in Arizona, U.S.
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