Researchers at Stanford have been using artificial intelligence (AI) to dive deeper into diabetes diagnosis — and the results could mean better, more accessible care.
We commonly understand diabetes as being either Type 1 or Type 2. But in recent years, scientists have discovered important variations, or subtypes, within Type 2 — which makes up 95% of diagnoses — that shed light on the risk of contracting related conditions, like kidney, heart, or liver issues.
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“Understanding the physiology behind [diabetes] requires metabolic tests done in a research setting, but the tests are cumbersome and expensive and not practical for use in the clinic,” explained Tracey McLaughlin, MD, an endocrinology professor at Stanford.
Using data collected by glucose monitors, researchers developed an algorithm identifying three of the four most common subtypes of Type 2 diabetes.
Compared to clinical data, the algorithm “predicted …