Natural Language Processing Utilisation in Healthcare

Abstract

The importance and usage of natural language processing (NLP) have grown a lot in the field of the medical domain for taking various clinical data for several clinical studies and clinical trials. By performing the trails much advancement was developed. Generally, NLP techniques were designed for developing word- and sentence-based searches and getting the best result as per the search criteria, for example, using keywords like disease names, medicine names, side effects of a particular drug or suggesting the drug based on symptoms of a person. Electronic health records (EHR) play a very major role in storing the patient’s medical records from time to time when they visit various doctors. The main advantage of EHR is it can track the history of the health records very easily. Based on the NLP and EHR techniques, general notes and suggestions will be given to the doctor for making the task simpler, and using this keyword search technique provides many advantages such as reducing time for disease identification, helping doctors make the correct decision, affording time for more patients, etc. Even though the NLP technique is performing such numerous things, there are some challenges to using the NLP technique in the medical domain where it needs to improve. For the EHR technique, many technical challenges have to be overcome such as resistance, performance, effectiveness in generating results, etc. Here in this chapter we are presenting a complete survey of NLP with its limitations and also how NLP is showing efficient results in the medical domain.