An Intelligent Machine Learning-Based Multi-Disease Prediction System with Chatbot

Early diagnosis of chronic diseases is crucial to improve healthcare results and mitigate medical risk. In the present paper, an intelligent system of machine learning-based multi-disease prediction with the integration of chatbot technology for healthcare support is proposed. The system predicts the risk of Diabetes, Parkinson’s disease, and Lung Cancer using machine learning and deep learning models. The system uses the XGBoost algorithm to predict Diabetes and Lung Cancer by analyzing structured medical data, while the EfficientNet CNN is used to predict Parkinson’s by analyzing handwriting images. The system is implemented using Python with libraries such as TensorFlow, Keras, and Scikit- learn. A chatbot module is integrated to provide basic health guidance and explain prediction results. Experimental results show that the proposed system achieves reliable prediction accuracy and supports early disease screening. The proposed approach demonstrates the potential of artificial intelligence to assist in accessible and intelligent healthcare decision support systems.