Deep Learning-Based Intelligent System for Multi-Disease Brain Analysis and Early Diagnosis Using Medical Imaging

This research presents an AI-powered diagnostic system designed to assist in the early and accurate prediction of brain-related diseases such as brain tumors, strokes, and Alzheimer’s disease. By leveraging the power of Convolutional Neural Networks (CNNs), the proposed model demonstrates significant potential in reducing diagnostic time, minimizing human error, and improving healthcare outcomes. The system automates the analysis of medical imaging data, offering a fast and reliable second opinion for healthcare professionals. Through effective preprocessing, model training, and performance evaluation, the system proves to be a promising step toward integrating artificial intelligence into real-world clinical practices. Furthermore, its accessible design and potential for deployment in under-resourced areas make it a valuable contribution to smart and inclusive healthcare. In the future, this system can be expanded to include more neurological conditions and integrated with hospital systems for large-scale use

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