Abstract: Skin diseases are widespread and require timely detection to prevent complications. However, access to dermatological care is limited in many regions, leading to delayed diagnosis and treatment. Derma-Scan is an AI-powered Android application designed to provide users with fast and reliable preliminary skin disease detection using smartphone-captured images. The system integrates a deep learning-based Convolutional Neural Network (CNN) model optimized with TensorFlow Lite to analyse skin images and predict potential diseases with high accuracy. The application offers an intuitive interface, real-time prediction, secure data handling, and a history feature for tracking user reports. Derma-Scan aims to support early screening, increase accessibility to dermatological insights, and assist users in making informed decisions regarding further medical consultation. This project demonstrates the potential of mobile AI solutions in healthcare, particularly in resource-constrained environments.
Keywords: Skin Disease Detection, Artificial Intelligence, CNN, TensorFlow Lite, Android Application, Medical Imaging, Dermatology, Deep Learning.
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DOI:
10.17148/IJARCCE.2026.15219
[1] Sagar Jadhav, Payal Unhale, Ritesh Koli, Aishwarya Chaudhari, "Derma Scan – Skin Disease Detection Using AI in Android," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2026.15219
