pak

>about 10% of people who come in to the cardiology clinic experiencing symptoms are diagnosed with an abnormal heart rhythm

OK, but I'd be more careful about staying apples to apples in your comparisons; your app is about asymptomatic AFib. So how many of those people going to the cardiology clinic had undiagnosed AFib; for how many of those would a new diagnosis of AFib have changed the plan of care; etc. Kind of like robbiep was saying, I would be interested in actual added value from the larger perspective.

Totally appreciate your point about perfect being the enemy of the good. The danger is that these semi-medical wearables currently straddle a strange zone between medical and consumer use. The inevitable marketing strategy is to co-opt the positive reputation of medical products while acknowledging none of the pitfalls of consumer products. Most of the screening methods you bring up are used by a doctor on symptomatic patients with a suggestive history, and only as a partial component of clinical judgement. The way Cardiogram seems to make the most money, on the other hand, is to sell the product to asymptomatic, casual users. (Furthermore, CHA2DS2-Vasc costs 30 seconds of talking or reading a medical record, not $700 in Apple products.) So you're inevitably running up against some doubts among physicians [0].

And finally, I agree that more machine learning practitioners should join medical research. I hope the field works to set more reasonable expectations, however, as in: ML will solve very specific subtasks in clinical reasoning (as in the diabetic retinopathy study [1]). Instead, the headlines usually ratchet that up to "AI will replace radiology/cardiology/$specialty in X years." That tends to hurt the people currently in the trenches, since their contribution in bringing about practical, incremental change is diminished. The top answer of this Quora thread [2] has a good discussion of the many dimensions of the problem.