AI-BASED SKIN LESION CLASSIFICATION AND REPORTING USING DEEP LEARNING

Abstract: Skin conditions can have similar visual characteristics, making preliminary assessment from images challenging. This paper presents a web-based Skin Disease Detector that combines a trained TensorFlow/Keras image- classification model with a Flask application. A user can create an account, upload a skin image, and receive three ranked class predictions with confidence scores. The system resizes images to 300 × 300 pixels, applies EfficientNet-compatible preprocessing, and passes the processed image to the loaded model. Results are stored in an SQLite database and can be revisited through prediction history. The application also provides disease information and downloadable PDF reports. The work demonstrates an end-to-end software implementation for educational and preliminary screening support. The supplied project files do not include a documented test dataset or evaluation metrics; therefore, no claim of diagnostic accuracy or clinical validation is made. The tool is not a substitute for examination by a qualified healthcare professional.

Keywords: deep learning, EfficientNet, image classification, skin lesions, web application