NLP: Syncing Language and Numbers in Healthcare

Original article was published by Samadrita Ghosh on Artificial Intelligence on Medium

Anybody not living under a rock in the 21st century is bound to have heard of Natural Language Processing or NLP. It is the technique of teaching machines to understand human-like languages in the most efficient manner. Wikipedia defines it as follows:

“Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.”

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The most fundamental obstacle which arises during the interchange of language between machines and humans is the fact that machines do not understand anything but numbers, and humans do not interact in numerical terms. This is where NLP comes to the rescue and bridges the gap between man and machines!

Every day, uncountable documents and transcripts are generated in the healthcare industry. Valuable information like medication details in prescriptions, data collected while tracking the vitals of patients and even the generic exchange of information involving patients and doctors can be greatly utilized if NLP comes to the aid.

Here are some of the most fundamental benefits that NLP has brought to the healthcare industry in general:

Speech recognition

Over the entire course of a day, it can become really difficult for doctors to take a note of every vital aspect during patient interaction. A simple NLP-supported voice recognition system can act as an AI assistant and provide doctors just what they need: tireless speed!

Clinical documentation improvement

As the volume of data in healthcare builds up with each passing moment, it becomes increasingly difficult to process the information. CDI helps to ensure that the information is correctly captured and stored accordingly for advanced processing.

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Data mining research

As is already known, the areas of research in healthcare is so vast, that experts spend lifetimes to understand even a drop in the big ocean. With the help of AI-assisted systems which can scrape reliable and relevant data off the web, given the requirements, the process of research is highly catalyzed with added efficiency.

Computer-assisted coding

Computer-aided coding systems study the available documents and identifies particular terms or phrases in the document, as in entity recognition. Thereafter, the identified unit is linked to an action item or a code as per requirement or relevance. Such coding is usually performed manually; however, it has been observed that the time taken for the process is significantly reduced when coders make use of computer-assisted coding.

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Clinical Decision Support

This is a relatively novel innovation and promises to provide knowledge and person-specific information which has been filtered skillfully and presented when and where required. The features can include notifications and reminders, patient summaries, clinical guidelines, references and several other such important vitals which can prove to be highly beneficial for not only patients and doctors, but also the staff in general.

These are just a set of basic NLP developments and are more like stepping stones to grander schemes. The power of NLP can be astounding and intense research has only narrowed down the gap between numbers and literature. It is only a matter of time before machines develop high proficiency in the languages of our world and start participating in all those conversations which can take us way forward.