Global natural language processing (NLP) in healthcare and life sciences market is accounted for USD 1.12 billion in 2017 and is projected to grow at a CAGR of 21.2% the forecast period of 2018 to 2025 (Current Year Statistic Will Be Provided in Report).
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Natural language processing (NLP) is the innovation which helps machines in understanding both written and spoken human language by analyzing human to computer collaboration. NLP strategies extraction of data from the large amount of clinical information and enhance it viably for improved preparing and examination. Because of this, various healthcare services suppliers are searching for arrangements that consolidate top of the line NLP innovations. Key Players in Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market are:
Others: Dolbey Systems, Fluxifi, HP, IBM, Linguamatics, Mmodal, Netbase, Nuance Communication, SAS Institute, Textalytics and Verint Systems. The global NLP in healthcare and life science market is fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market in order to sustain in long run. The report includes market shares of NLP in healthcare and life science Industry for global, Europe, North America, Asia Pacific and South America. The market report contains data for historic years 2016, the base year of calculation is 2017 and the Natural Language Processing (NLP) in Healthcare and Life Sciences industry forecast period is 2018 to 2025.
- NLP is also a piece of AI. It is both based on text and speech provided to the computer. Right now, NLP approaches depend on machine discovering that utilizations designs for understanding own projects.
- The most widely recognized NLP in all the product bundles incorporates sentence division, part of speech tagging and parsing, deep analytics, name entity extraction, co-reference resolution
The objective of NLP is to lessen the ideal opportunity for understanding coding languages, for example, Java, C, C++, and Ruby. The advancements of NLP arrangements is troublesome on the grounds that PCs require people to talk in a programming language that should be exact, unambiguous, and exceedingly organized with less measure of articulated voice commands. Nonetheless, human discourse can’t be exact, and it is often unambiguous and relies upon factors that incorporate slang, regional dialects, and social context.
- The global NLP in healthcare and life science market is based on
- Deployment model
- Geographical segments
- Based on component, the global NLP in healthcare and life science market is segmented technology and services.
- Technology is further sub segmented into interactive voice response (IVR), optical character recognition (OCR), pattern and image recognition, auto coding, classification and categorization, text analytics and speech analytics.
- Service is further sub segmented into support and maintenance and professional services.
- Based on type, the global NLP in healthcare and life science market is segmented into
- Based on application, the global NLP in healthcare and life science market is segmented into
- Machine Translation
- Automated Information Extraction
- Report Generation
- Predictive Risk Analytics
- Others (Question Answering, Dialogue Systems, Email Filtering, Spelling Correction, And Search Engine)
- Based on deployment model, the global NLP in healthcare and life science market is segmented into
- Based on Geography, the global NLP in healthcare and life science market report covers data points for 28 countries across multiple geographies such as North America, South America, Europe, Asia-Pacific and Middle East & Africa.
- Some of the major countries covered in this report are U.S., Canada, Germany, France, U.K., Netherlands, Switzerland, Turkey, Russia, China, India, South Korea, Japan, Australia, Singapore, Saudi Arabia, South Africa, and Brazil among others.
Market Drivers and Restraints:
- Effective utilization of internet and its web based applications.
- Emerging influence of big data and a vast amount of unstructured clinical data drives the growth of NLP in healthcare sector.
- Increased usage of connected devices.
- A challenging factor which is being faced by the healthcare and life sciences field incorporates the difficulties postured by government standards and controls.
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