Source: Upstartsmedia
AI systems trained predominantly on male patient datasets are reproducing historical medical blind spots rather than correcting them. Endometriosis and autoimmune disorders remain underdiagnosed because the algorithms learned from imbalanced cohorts. When Mayo Clinic or Cleveland Clinic deploy these models, they scale up bias at clinical decision points where women patients already face diagnostic delays averaging years. Health tech companies and hospitals have yet to invest in representative datasets or acknowledge that adequate performance for men is inadequate for half the population. AI adoption in women's health will deepen existing inequities rather than democratize care.