"AI-Driven Dermatology Could Leave Dark-Skinned Patients Behind" - Angela Lashbrook
As the rates of melanoma for all Americans continue a 30-year climb, dermatologists have begun exploring new technologies to try to reverse this deadly trend—including artificial intelligence. There’s been a growing hope in the field that using machine-learning algorithms to diagnose skin cancers and other skin issues could make for more efficient doctor visits and increased reliable diagnoses. The earliest results are promising—but also potentially dangerous for darker-skinned patients. An issue is that decades of clinical research have focused primarily on people with light skin, leaving out marginalized communities whose symptoms may present differently. The reasons for this exclusion are complex. According to Andrew Alexis, MD, MPH, director of the Skin of Color Center at Mount Sinai and chair of the department of dermatology at Mount Sinai St. Luke’s and Mount Sinai West, compounding factors include a lack of medical professionals from marginalized communities, inadequate information about those communities, and socioeconomic barriers to participating in research. “In the absence of a diverse study population that reflects that of the U.S. population, potential safety or efficacy considerations could be missed,” he says.
- Andrew Alexis, MD, MPH, Associate Professor, Dermatology, Icahn School of Medicine at Mount Sinai, Director, The Skin of Color Center at Mount Sinai, Site Chair, Department of Dermatology, Mount Sinai St. Luke’s-Mount Sinai West