NLP In Healthcare And Life Sciences Industry 2020 is excepted to reach USD 5,614 million by 2030

 Natural Language Processing (NLP) is a field in computer science, artificial intelligence, and computational linguistics for healthcare and life sciences that gives computers the ability to understand human speech as it is spoken. This allows for the development, management and use of a wide range of semi-structured and unstructured textual documents by clinical and research medical community. Applications of NLP for healthcare and life sciences include processing of enormous amounts of data by utilizing high-end NLP technologies for information extraction, automatic speech recognition, machine translation and dialogue systems.

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Market Highlights
The market for NLP in healthcare and life sciences is projected to exceed USD 5,614 million by 2030 from 1,442 million in 2019, at a CAGR of 20.81% throughout the forecast period i.e. 2020-2030. The market is anticipated to grow on the back of growing adoption of EHR.
The proliferation of data amounting in healthcare companies has forced vendors to adopt NLP solutions and help clinicians, researchers, and physicians to simplify and manage their decision-making process. NLP solutions enable healthcare providers to gain access to social media data from clinical reports, search engines and sites, such as Facebook, Twitter that enable organizations to fine tune their service experiences for patients.

The NLP in healthcare and life sciences market across the globe is mainly driven by the considerable rise in terms of volume of the unorganized clinical information. Growing adoption of the Electronic Health Records (EHR) systems in the 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.