Health Care Chatbot using Natural Language Processing with SGD and ADAM Optimizer Parameter Optimization

Abstract

In today’s world, everyone is not quite sure about the medicine that the users used in a similar situation or critical situation where any medical emergency has come and as all know that the ratio of patients and doctors are very high so, there is a requirement of such kind of applications to help in case of emergency. This paper proposed a novel approach for medical needs, as well as the suggested chatbot that will be useful in the pandemic circumstances. Natural Language Processing (NLP) based applications are proposed to provide help to the patient. In some situations, the patient home member just used it to type their query and if the patient situation is not so serious, so they get proper medicinal information from this application. The proposed methodology takes an input sentence then its tokenization, removal of stop words, feature extraction, and word corpus are used to find the sentence similarity, and the chatbot predicts the accurate sentence. In this work, the Stochastic Gradient Descent (SGD) and Adaptive Moment Estimation (ADAM) optimizer optimized parameter values are determined with 86 and 93 percent accuracy respectively. The optimized Lr_value 0.0099 and Decay value 1e-10 for SGD and optimized Learning_rate 0.0099 for ADAM are obtained.