DiagnoBot: A Medical Chatbot

Abstract

Many people live without access to healthcare or delayed care due to inconvenience, work, cost, living in rural areas, or social/medical fears Gertz et al., 2022, Golembiewski et al., 2022. Medical chatbots have emanated as a potential solution to healthcare access and to promote self-care. We aim to provide medical information through conversations with those who may otherwise delay seeking care. A Rasa chatbot is created using our Disease Prediction System, which utilizes machine learning algorithms i.e., Decision Trees, Gradient Boosting, Support Vector Machine (SVM), and Naïve Bayes to guide users to a sensible diagnosis, so they may opt for self-care at home or seek medical attention. In this paper, a sample of 4920 patient records with 41 disorders are analyzed. The Recursive Feature Elimination algorithm enhances 95 out of the 132 symptom features. Our system achieved 97-100 percent accuracy.