The role of natural language processing in modern healthcare

Natural Language Processing (NLP) has applications in several industries.

Not surprisingly, the field of health is no different. NLP’s involvement in healthcare promises to increase further in the future.

Natural language processing, or NLP, is a subdomain of AI that performs text generation, automated manipulation of natural language in speech and text, and a few other applications. NLP is a vital cog in AI, which promises to take smart technology to new heights in the future. Modern healthcare has benefited greatly from NLP and will continue to do so. Here, we’ll look at some of the ways that including NLP in healthcare is helping physicians, patients, and others in the field:

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Improve clinical documentation in hospitals

As we know, hospitals and clinics need to constantly maintain and update their patient records from time to time. NLP-assisted clinical documentation allows physicians and other hospital and clinic staff to focus on their core tasks (patient care, customer service) and let NLP handle the arduous task of updating EHRs. for each patient. NLP-based healthcare tools allow them to use the text-to-speech conversion capabilities of the system for efficient data entry. In combination with IoT powered tools such as sound detection sensors, NLP can use its speech recognition and language skills to dramatically improve documentation work in hospitals.

Facilitate root cause analysis in healthcare

The inclusion of NLP in health care may also involve tools such as predictive analytics systems to identify and resolve health problems of the general public. Health officials can use a combination of NLP and AI to browse vast expanses of digitally presented electronic medical records to categorize individuals based on their ethnicity, location, and other population factors. . These classifications can be used to detect and analyze the different health problems faced by people in certain regions or by those belonging to specific ethnicities. Governments and mainstream healthcare organizations are currently unable to shed light on some unexplained socio-cultural medical conditions in people, but NLP and predictive analytics may open up new avenues of research to address these root cause issues.

Help with clinical trial matching

As we know, finding the right patients to conduct clinical trials of new drugs or vaccines can be a challenge for researchers. Systems powered by NLP and computer vision tools can help health experts do the same. Such systems quickly scan the past medical records of these patients before confirming whether they are fit to participate in trials or not.

NLP can provide exceptional support to AI systems in healthcare with its incredible language and text generation capabilities. While NLP’s contributions to healthcare may not be glaring enough to some, technology is slowly but surely revolutionizing the field.


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