Authors : Ashish Zagade; Vedant Killedar; Onkar Mane; Ganesh Nitalikar; Smita Bhosale

Volume/Issue : Volume 9 - 2024, Issue 3 - March

Google Scholar : https://tinyurl.com/4pr55hmk

Scribd : https://tinyurl.com/ysaksj5n

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAR804

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This research paper presents the development and implementation of an AI-based medical chatbot for disease prediction. Leveraging machine learning and artificial intelligence technologies, the chatbot utilizes natural language processing (NLP) to understand user queries and provide accurate information, guidance, and assistance for various infectious diseases. Motivated by the global spread of infectious diseases and the need for accessible healthcare support, the paper outlines the objectives, algorithm design, dataset description, and application of the chatbot. The algorithm involves receiving user input, extracting symptoms, classifying diseases, and suggesting prevention measures. The dataset, structured in JSON format, facilitates training and pattern recognition. The chatbot interface, accessible across platforms, offers information on symptoms, prevention measures, hospital bed availability, and medication options. In conclusion, the research highlights the potential of AI-based chatbots in revolutionizing healthcare accessibility and personalized diagnosis, thereby bridging the gap between users and healthcare systems.

Keywords : AI-Based Chatbot, Disease Prediction, Machine Learning, Natural Language Processing (NLP), Healthcare Accessibility, Infectious Diseases, Personalized Diagnosis, Healthcare Support.