Natural Language Processing And Its Use In Health Sector Pdf

natural language processing and its use in health sector pdf

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Mobile health m-health is the term of monitoring the health using mobile phones and patient monitoring devices etc. It has been often deemed as the substantial breakthrough in technology in this modern era. Recently, artificial intelligence AI and big data analytics have been applied within the m-health for providing an effective healthcare system.

Natural Language Processing in Healthcare – Current Applications

Natural Language Processing, or NLP for short, is broadly defined as the automatic manipulation of natural language, like speech and text, by software. Or in rather simple terms, we may divide the term into Natural Language and Processing. Natural language refers to the way we, humans, communicate with each other. Namely, speech and text. We are surrounded by text. Think about how much text you see each day:.

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Several developments in the healthcare sector, such as escalating healthcare costs, increased need for healthcare coverage, and shifts in provider reimbursement trends, trigger the demand for big data technology. The wide scope and variety of discussed big data applications indicate the promising opportunities of big data technologies to improve overall healthcare delivery. However, in order to realize those applications, one needs to enable seamless access to the various health data sets. As of today, access to health data is only possible in a very constrained and limited manner. In order to improve this situation and for establishing the basis for the widespread implementation of big data applications in the healthcare sector, several technical requirements such as the semantic enrichment of data, data integration and sharing, data privacy and security, as well as data quality, need to be addressed. In terms of market adoption, the big data revolution in the healthcare domain is in a very early stage with the most potential for value creation and business development unclaimed as well as unexplored.

This article explores some new and emerging applications of text analytics and natural language processing NLP in healthcare. Each application demonstrates how HCPs and others use natural language processing to mine unstructured text-based healthcare data and then do something with the results. Healthcare databases are growing exponentially, and text analytics and natural language processing NLP systems turn this data into value. Healthcare providers, pharmaceutical companies and biotechnology firms all use text analytics and NLP to improve patient outcomes, streamline operations and manage regulatory compliance. In fact, 26 million people have already added their genetic information to commercial databases through take-home kits.


An overview is given of natural language processing applications in medicine. (NLP) in medicine as one of the most challenging issues in the field of management system for health care applications in the hospital.


Big Data in the Health Sector

When it comes to the healthcare industry, one might be able to think of numerous use cases for AI approaches like machine vision or predictive analytics. Founded in , Connecticut startup IQVIA offers a namesake software platform that they claim helps healthcare companies keep up with changes to industry compliance requirements. They also claim it can account for safety and quality compliance, as well as for healthcare industry and commercial regulations. This engine purportedly makes use of both predictive analytics and NLP to comb through data and find the information the user is looking for. As a result, NLP could help to make sense of information that could prove valuable to a client.

Natural Language Processing poses some exciting opportunities in the healthcare space to swim through the vast amount of data currently untouched and leverage it to improve outcomes, optimize costs, and deliver a better quality of care. The branch of AI seems to be critical for navigating through the growing volume of data already in silos and generated daily. The article outlines the factors that are driving the growth and implementation of Natural Language Processing in healthcare, the plausible benefits of the implementation and the future of Artificial Intelligence and Machine Learning in healthcare. Natural Language Processing can be stated in layman terms as the automatic processing of the natural human language by a machine. It is a specialized branch of Artificial Intelligence which primarily focuses on interpretation as well as human generated data — text or speech based.

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NLP in Healthcare? Sure, It’s a thing!

As a human, you may speak and write in English, Spanish or Chinese. Indeed, programmers used punch cards to communicate with the first computers 70 years ago. This manual and arduous process was understood by a relatively small number of people. Then it adapts its algorithm to play that song — and others like it — the next time you listen to that music station. Your device activated when it heard you speak, understood the unspoken intent in the comment, executed an action and provided feedback in a well-formed English sentence, all in the space of about five seconds. The complete interaction was made possible by NLP, along with other AI elements such as machine learning and deep learning. Royal Bank of Scotland uses text analytics , an NLP technique, to extract important trends from customer feedback in many forms.

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This website uses a variety of cookies, which you consent to if you continue to use this site. You can read our privacy policy for details about how these cookies are used, and to grant or withdraw your consent for certain types of cookies. Consent and dismiss this banner by clicking agree. Despite the uncertain atmosphere — or, in some cases, because of it — healthcare providers are taking the opportunity to beef up their big data defenses and develop the technological infrastructure required to meet the impending challenges of value-based reimbursement, population health management, and the unstoppable tide of chronic disease. Analytics are already playing a major part in helping providers navigate this transition, especially when it comes to the revenue and utilization challenges of moving away from the fee-for-service payment environment. But clinical analytics and population health management have been a trickier mountain to climb.


New initiatives, such as the Health Natural Language Processing (hNLP) the field of mental health has shown a burgeoning increase in the use of NLP Moreover, for some clinical use-cases, patient-level annotations by e.g., manual chart.


Top 12 Use Cases of Natural Language Processing in Healthcare

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