SmartScan+ is an AI-based medical screening system developed as a Final Year Project (FYP) for the BS Computer Science program. The project focuses on early risk detection of skin lesions and anemia using computer vision and deep learning techniques.
The project demonstrates the practical application of artificial intelligence in healthcare by integrating machine learning models with mobile and web-based systems to support preliminary medical screening.
Deep learning models analyze medical images to estimate the likelihood of skin lesion categories and anemia-related visual indicators.
The models are trained using publicly available and research-backed medical datasets to ensure reproducibility and academic validity.
The solution includes mobile image acquisition, backend processing, AI inference, and a web-based results dashboard.
SmartScan+ is designed as a decision-support and preliminary screening tool. It aims to assist users and healthcare professionals by providing early risk indications rather than definitive medical diagnoses.
The system follows a modular and scalable architecture separating data capture, AI processing, backend services, and user interfaces.
SmartScan+ provides probabilistic outputs based on trained datasets. The system is not a substitute for professional medical diagnosis and should be used responsibly.