Skin diseases affect nearly one-third of the global population, yet dermatologists are in critically short supply, with wait times often exceeding three months. A new scientific review argues that smarter AI can help bridge this gap.

The paper introduces “AI Dermatology 2.0”, a fundamental shift from pattern-matching AI (which only answers “what”) to causal reasoning AI that answers “why”. Causal algorithms improved rare skin disease diagnosis by up to 32.9% in tests, while “skin digital twins” enable virtual drug trials and 72-hour eczema flare predictions with over 90% accuracy.

AI 2.0 also acts as an intelligent collaborator, raising primary care diagnostic accuracy from 73% to 82% and potentially cutting the 10-year average diagnosis delay for hidradenitis suppurativa. Crucially, it will not replace dermatologists but free them to become “system commanders” focused on complex cases and patient care. “AI 2.0 redefines how we practice dermatology”, said corresponding author Prof. Yang Yang. “By shifting to proactive risk interception, we can move toward lifelong skin homeostasis for all patients.”

The work titled “Dermatology AI 2.0: A Paradigm Shift Towards Causal Inference, Precision Forecasting, and Autonomous Intelligence” was published in Skin on May 11, 2026.
DOI：10.2738/SKIN.2026.0004