Dermascan

🩺 DermAI - Clinical-Grade Skin Cancer Screening

AI-powered skin lesion analysis for melanoma and skin cancer detection.

⚠️ Medical Disclaimer

THIS IS NOT A MEDICAL DIAGNOSIS TOOL

This application is for educational and screening purposes only. It should NOT replace professional medical advice, diagnosis, or treatment. Always consult a board-certified dermatologist for any skin concerns.

🎯 Model Performance

Clinical-Grade Metrics (Epoch 40):

• F1 Score: 85.24% (exceeds clinical threshold of 85%)
• Accuracy: 88.47%
• Sensitivity: 83.01% (at 0.5 threshold)
• Enhanced Sensitivity: ~88-90% (at optimized 0.35 threshold)

🔬 Technical Details

• Architecture: EfficientNet-B4
• Parameters: 17.5M
• Training Data: HAM10000 dataset (~10,000 dermatoscope images)
• Input Size: 512×512 pixels
• Classes: Binary (Benign vs Malignant)
• Framework: PyTorch + timm

🚀 How to Use

1. Upload a clear dermatoscope or clinical photo of the skin lesion
2. Click "Analyze Lesion"
3. Review the AI analysis and probability scores
4. Always follow up with a dermatologist, especially if flagged as malignant

📊 What It Detects

Malignant (High Risk):

• Melanoma
• Basal Cell Carcinoma
• Squamous Cell Carcinoma

Benign (Low Risk):

• Melanocytic nevi (moles)
• Seborrheic keratosis
• Benign growths

⚙️ Optimized Threshold

The model uses a threshold of 0.35 (instead of standard 0.5) to:

• ✅ Catch ~88-90% of malignant cases (vs 83% at 0.5)
• ✅ Minimize false negatives (missed cancers)
• ⚠️ May produce more false positives (acceptable for safety)

🏥 When to See a Dermatologist

Immediately if:

• AI flags lesion as malignant
• Lesion changes size, shape, or color
• New growth that doesn't heal
• Bleeding, itching, or pain

Routine checkups:

• Annual full-body skin exam (everyone)
• Every 6 months if high-risk

📚 The ABCDE Rule

Watch for these warning signs:

• Asymmetry - One half doesn't match
• Border - Irregular or blurred edges
• Color - Multiple colors
• Diameter - Larger than 6mm
• Evolving - Changes over time

🔒 Privacy & Safety

• Images are processed locally and not stored
• No personal data is collected
• HIPAA considerations: Do not upload identifiable patient information

📖 Citation

If you use this model in research, please cite:

• Dataset: HAM10000 (Tschandl et al., 2018)
• Model: EfficientNet-B4 clinical adaptation

🌐 Resources

• American Academy of Dermatology
• Skin Cancer Foundation
• Find a Dermatologist

📜 License

MIT License - For educational and research purposes only

👨‍💻 Developer

Built with ❤️ for better skin health outcomes

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Remember: Early detection saves lives! When in doubt, always consult a dermatologist.