DermaScan — AI Skin Disease Classification
CNN-based analysis of clinical skin images returns a ranked list of likely conditions with confidence scores and guideline prompts; designed for EMR/telederm integration and continual learning.
Overview
DermaScan is an AI-powered diagnostic support tool that analyzes clinical skin photographs and returns a ranked list of likely conditions with associated confidence values. The system performs lesion detection and classification across common and serious dermatoses and can attach guideline-aligned suggestions to assist triage and management. It is built for integration with EMR and teledermatology platforms and supports continual learning with expert feedback so accuracy improves over time.
Clinical Problem
Shortages of dermatology specialists, especially in rural and resource-limited areas, lead to under- or misdiagnosis and delayed care. Primary-care and telehealth providers often lack automated support to prioritize risk or to standardize documentation. A system that can rapidly examine images, suggest differential diagnoses and provide guidance can improve access, triage and outcomes.
Methodology
- Train CNN models on diverse, labeled datasets covering a wide range of dermatologic conditions.
- Detect lesions and perform multi-class classification to produce a ranked list with confidence scores.
- Return guideline-linked hints and export structured outputs for EMR/telemedicine use; collect expert feedback to improve models.
Tech Stack
Equipment
Expected Outcomes
Training/validation underway; pilots with dermatology departments to benchmark clinical accuracy.