FDA Clears A Skin Cancer Scanner. It Misses The Obvious Stuff. Specificity Is The Whole Job, Obviously.
Dr. Jules B. Lipoff discusses real-time AI deployment in dermatology. DermaSensor, an FDA-cleared screening tool for primary care, shows high sensitivity but low specificity. Most convolutional neural network studies analyzed curated image sets retrospectively rather than in live clinical workflow.
This illustrates the sensitivity-specificity tradeoff. A tool that catches every possible malignancy also flags countless benign lesions. High sensitivity without matching specificity creates alarm fatigue and unnecessary biopsies. The lesson: a single metric never defines a good clinical tool.
Dr. Jules B. Lipoff, MD, addresses AI integration in dermatology practice. DermaSensor by DermaSensor, Inc. holds FDA clearance for primary care skin cancer screening.
- Go to chatgpt.com or any free AI chatbot. Upload a close-up photo of a mole or skin mark and ask 'What might this be?'
- Ask the same AI 'What are ten other things that look similar?' You will get a long list.
- Notice how the AI flags many possibilities but cannot narrow them down. That gap between flagging everything and pinpointing one diagnosis is the specificity problem Dr. Lipoff describes.