Algorithms, apps, and smart wearables are supposed to make medicine more precise, personalized, and accessible. But for whom does digital medicine actually work? This talk demonstrates that health is neither biologically nor socially gender-neutral—and that these differences are embedded in digital applications: in diagnostic algorithms that are less reliable for women, in sensors calibrated for specific body types, and in training data that has long primarily reflected men.

By examining three gaps—data, access, and policy—the talk analyzes how eHealth reinforces existing inequalities, for example through the digital gender gap, varying levels of digital health literacy, or the lack of guidelines in the EU AI Act. At the same time, the presentation highlights examples where gender-sensitive design is already succeeding—from cardiovascular risk assessment to femtech to digital mental health services—and introduces a five-level model for how digital medicine can work for everyone.