Deep Learning Approaches for Brain Disease Diagnosis.

The rising incidence of neurological disorders such as Alzheimer's, Parkinson’s, and brain tumors has underscored the need for intelligent diagnostic tools. This work introduces NeuroNet AI, a user-centric application that leverages deep learning models for brain disease classification using MRI images. Users begin by registering and logging into the app. Upon uploading a brain MRI scan, the image undergoes preprocessing and is then classified using a trained convolutional neural network (CNN) into one of several categories: Alzheimer's, Parkinson’s, tumor, or normal. The prediction result is accompanied by a brief description of the condition, with an option to explore more via a Wikipedia link. This application simplifies the diagnostic journey for users and fosters awareness of neurodegenerative disorders. By combining automation, accuracy, and accessibility, NeuroNet AI offers a smart interface for preliminary brain health analysis. The tool is especially useful in raising awareness and guiding further consultation with professionals.

Keywords: Brain MRI, Deep Learning, Disease Classification, Image Preprocessing, Neural Networks, Prediction System.