No quote in particular, but it seems unlikely that they would miss such a blatant dataset bias and fail to instrument their ML models with metrics besides accu

No quote in particular, but it seems unlikely that they would miss such a blatant dataset bias and fail to instrument their ML models with metrics besides accuracy. But then again, welcome to Silicon Valley :) 1 - 200/6158 = 97% is indeed a pretty suspicious coincidence though. I would assume/hope that they've shuffled a big dataset of recorded heart events (like the image in the TC article) and that the 200 people diagnosed with paroxysmal atrial fibrillation only rarely experience AF, so the number of true positives is probably far smaller than 1% of the dataset.