AI-Powered Healthcare Chatbot using T5 for query Responses and Random Forest for Symptom-based Diagnosis with Voice and Text Output Healthcare, Medical Diagnosis

This work introduces the MediChat AI which is a medical chatbot that is an intelligent multilingual system based on natural language processing, speech recognition and real-time translation as a way to make healthcare more accessible. Developed on the basis of the T5 Transformer model adjusted to medical question answering and a Random Forest classifier to predict the disease based on the symptoms, MediChat AI is able to respond to all types of questions both textually and verbally and respond to them correctly and within context. The system uses the Google Translator APIs to support multiple languages and the use of the gTTS to give voice response which allows easy interaction between the patients and the artificial intelligence assistant. It also has an option of speech-to-text wherein voice queries are processed. The project reflects the successful combination of deep learning and rule-based inference with multilingual processing in order to obtain accessible medical consultation. As the experimental outcomes prove, the suggested system presents an efficient interactive and reliable healthcare dialogue support that can be used by users all over the world.