Judge skin cancer AI by the thick melanomas it prevents, not the thin ones it finds
Melanoma diagnoses have soared while deaths barely changed, a sign of overdiagnosis. AI skin apps should be judged on whether dangerous thick melanomas fall, not how many spots they flag.
Melanoma incidence has risen roughly six-fold in the US since 1975 with much smaller mortality change. AI dermatology tools risk amplifying detection of indolent in-situ lesions. Propose that regulatory and reimbursement evaluation of AI skin triage require thick (over 1 mm) melanoma incidence and biopsy-to-melanoma ratio as endpoints.
- Overdiagnosis and false alarms · Finding more cancer is not the same as saving lives. Screening also finds cancers that would never have hurt anyone, and treats them.
- AI that is built but not validated or deployed · Thousands of cancer AI models are published; a handful are in clinical use, and fewer have shown they help patients.
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not linked directly; found by shared links- IdeaAI malignancy scores to end repeat scans and biopsies for benign lung nodules
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- IdeaAI second reads to stop borderline lesions being upgraded to cancer
Shares Overdiagnosis and false alarms, AI that is built but not validated or deployed.
- IdeaRequire stage-shift or interval-cancer endpoints for AI in cancer screening
Shares Overdiagnosis and false alarms, AI that is built but not validated or deployed.
- InstitutionDartmouth Cancer Center
Shares Overdiagnosis and false alarms, Melanoma.
- Key paperMASAI: AI-supported mammography screening finds more cancers with half the radiologist workload
Shares Overdiagnosis and false alarms, AI that is built but not validated or deployed.
- TechnologyDermoscopy, total-body photography & AI skin analysis
Shares AI that is built but not validated or deployed, Melanoma.