Dermatologist Harald Kittler draws on more than a decade of experience when he teaches students at the Medical University of Vienna how to diagnose skin lesions. His classes this fall will include a tip he learned only recently from an unusual source: an artificial intelligence algorithm.
That lesson originated in a contest Kittler helped organize that showed image analysis algorithms could outperform human experts in diagnosing some skin blemishes. After digesting 10,000 images labeled by doctors, the systems could distinguish among different kinds of cancerous and benign lesions in new images. One category where they outstripped human accuracy was for scaly patches known as pigmented actinic keratoses. Reverse engineering a similarly trained algorithm to assess how it arrived at its conclusions showed that when diagnosing those lesions, the system paid more than usual attention to the skin around a blemish.
Kittler was initially surprised but came to see wisdom in that pattern. The algorithm may detect sun exposure on surrounding skin, a known factor in such lesions. In January, he and colleagues asked a class of fourth-year medical students to think like the algorithm and look for sun damage.
The students’ accuracy at diagnosing pigmented actinic keratoses impr
