Healthcare chatbot using machine learning and natural language processing

Healthcare is a fundamental necessity and a basic right of every human. Major advancements, like the development of healthcare chatbots, are transforming the healthcare industry. They help individuals who cannot consult doctors for every minor ailment by providing timely assistance. By helping users assess health concerns and providing relevant information, chatbots reduce unnecessary doctor visits. The purpose of this study is to create a healthcare chatbot that leverages advanced technologies such as Natural Language Processing (NLP) to efficiently process user inputs. It guides users through a series of questions to identify their symptoms and uses Machine Learning (ML) to suggest possible health conditions. The system incorporates an ensemble learning approach using majority voting among K-Nearest Neighbors (KNN), AdaBoost, and Multi-Layer Perceptron (MLP), achieving an accuracy of 96.47%. Additionally, it offers personalized recommendations such as disease descriptions, precautions, diet plans, exercise plans, medications, and suggests doctors based on the user's location, providing essential details to help them find the right healthcare professional. By relieving the burden on doctors for minor health concerns, the chatbot contributes to a more streamlined healthcare system, ensuring healthcare resources are allocated effectively for serious medical cases and enabling users to manage their health with a virtual assistant available around the clock.