Design and Implementation of Medical QA System using Machine Learning Techniques

Nowadays, people rely on Traditional books or Google for every answer to their questions on a day-to-day basis, from basic information to medical queries. Till now, people are facing problems and are unable to find the accurate answer to their questions or fetch relevant results. Also, this technique is time-consuming as people have to go through many books to obtain one relevant answer or search various websites, which is a tedious task and not an efficient way in today's world where time is the top priority, yet the majority of people follow these techniques. So, to overcome this technique and solve the current problems, we have implemented a new technique in this paper. The BERT model, pre-trains deep bidirectional representations from the unlabeled text which conditions on both left and right, as a result, provides accurate answers to the user’s query when compared to the state-of-the-art model. This same model can be further implemented in other domains to obtain accurate results.