AI for Rare Disease Diagnosis via Skin and Eye Images

Abstract

The study aims to create a system based on artificial intelligence (AI) to early and correctly diagnose rare diseases. It targets skin and eye conditions by analyzing images. The system utilizes cutting-edge technology in the form of deep learning models such as Deep Q-Networks, InceptionResNetV2, and the Swin Transformer Model. These technologies enable the identification of various types of diseases from images with great accuracy. The AI system is trained on high-quality sets of images of unusual skin and eye diseases. It’s available via a simpleto- use website that allows users to upload photos in real-time and query symptoms via a chatbot. The tool is intended to help doctors and patients detect diseases early, which can lead to quicker treatment and improved health outcomes. The project aims to offer a reliable and user-friendly tool to make the identification of rare diseases more accessible, shorten the time to diagnose them, and promote early treatment. It can potentially be used not just as an aid in delivering diagnoses but also as a means to increase access to AI-based healthcare in regions with insufficient medical services.