International Journal of Scientific Research and Engineering Development

This study is dedicated to detecting multiple diseases in human organs such as the brain, lungs, breasts, stomach, and skin by leveraging deep learning techniques. We implemented Convolutional Neural Networks (CNNs) to train a dataset, facilitating a comprehensive comparison and analysis, given that CNNs are highly effective for image recognition tasks. In our investigation, we utilized a CNN in conjunction with advanced image processing methods to scrutinize medical images. We evaluated the performance of our custom CNN model against dense models and found that, despite the limited size of our dataset, our model achieved remarkable accuracy, reaching 90% with minimal complexity. Unlike existing pre-trained models, our CNN model not only requires fewer computational resources but also achieves significantly higher accuracy.

Pranita Paul, Vineet Digge, Shreya Rokade, Vinayak Koli, A. P. Hosale,"Multi Disease Detection Using Deep Learning Model" International Journal of Scientific Research and Engineering Development, V9(3): Page(203-206) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.