Abstract

This study focuses on leveraging machine learning techniques to develop efficient, accessible disease prediction models, transforming healthcare delivery. A comprehensive dataset consisting of medical history, genetic factors, lifestyle attributes, and environmental variables is meticulously processed to ensure accuracy. Various AI models, including decision trees, random forests, support vector machines, and deep learning algorithms, are utilized to create predictive healthcare solutions. By integrating cutting-edge approaches such as cross-validation and hyperparameter tuning, the project aims to enhance early disease detection, reduce healthcare burdens, and promote preventative strategies.