Skincare AI - Skin Disease Detection Platform

Built an intelligent web platform that leverages computer vision and deep learning to help users identify potential skin conditions through image analysis. Developed with Next.js for a responsive frontend and Python-based Convolutional Neural Network (CNN) architecture for the backend, the platform allows users to upload skin images and receive instant AI-powered disease detection results. The system processes images through a trained CNN model that classifies various skin conditions with high accuracy, providing users with detailed insights about potential dermatological issues. The application features an intuitive user interface that guides users through the upload process, displays results with confidence scores, and offers educational information about identified conditions to promote skin health awareness.

The technical implementation combines modern web technologies with robust machine learning infrastructure to ensure scalability and accuracy. The Next.js frontend handles image uploads and real-time result visualization, while the Python backend processes images through a sophisticated CNN model optimized for dermatological classification. The architecture includes proper image preprocessing, model inference optimization, and API integration between the frontend and backend services to deliver fast, reliable predictions. Security and privacy are prioritized through secure image handling and user data protection, ensuring sensitive medical information remains confidential. This project demonstrates full-stack development capabilities, from creating an engaging user experience to implementing production-grade machine learning solutions for healthcare applications.