[northern_lights]

To address your example directly - we already have holter monitors that would show a case of atrial fibrillation quite easily. They aren't terribly expensive, at least for something that has to have FDA approval, and they are frequently used. Heck, you don't even need "AI," in the sense of neural networks/machine learning/some other buzzword. Current systems will review a strip collected over several days and flag any abnormal rhythms.

The problem comes with determining who to put on a monitor. In the case of the patients you described, it's actually quite likely that the doctors seeing these patients considered the possibility of afib. The symptoms, though, can be very vague, and they are seen nearly every day in the doctor's office. It's simply too expensive to put every patient on a holter monitor - the doc's office has to be paid to maintain the monitors (which people abuse at home), the nurses have to be paid to teach patients how to correctly wear them, the monitor company has to be paid for whatever absurdly expensive and proprietary review software they supply, and the prescribing doctor (oftentimes the prescribing cardiologist) has to be paid to review and confirm the machine's interpretation.

All of this for a transient rhythm which any second year medical student would easily recognize if presented the EKG from across the room.

The sad reality is that the patients you described were experiencing the system as it is "designed" (I use the term loosely) to work. The fact that someone is persistently seeking help for their problem dramatically raises the probability that something is truly wrong, and doctors actually recognize this and take it into account. This is one of the reasons it's considered best practice to establish a long term relationship with one doctor who knows you well, but it's harder and harder to do with insurance companies only reimbursing for 15 minute visits.