Health Assistance System for Brain Disease Detection Using ML

This study examines the utilization of machine learning techniques for the diagnosis of multiple diseases, aiming to revolutionize diagnostic processes. This project contains detection of diseases such as Parkinson’s, Alzheimer, Mental Ailment and Stress Level. Leveraging diverse variety of datasets and using advanced algorithms, this research indulges into the development of a predictive model which is capable enough to identify the particular disease at it’s earliest stage and also classify such conditions. By examining various medical indicators, imaging data or information, and symptomatology, the proposed framework demonstrates promising accuracy in detecting abnormalities in the nervous system. Furthermore, this abstract also discusses about the stage of the disease, preferred remedies and therapies derived from the detected patterns, facilitating precautions and focused treatments. The combination of machine learning with medical diagnostics not only enhances early detection but also opens ways for personalized therapeutic strategies, treatments and potentially bringing a change in the management and cure of nervous disorders and abnormalities.