mcflyanddie

joined 10 months ago
[–] mcflyanddie@alien.top 1 points 10 months ago

As both a medical doctor and someone completing a PhD in ML applied to healthcare, I'm a little sceptical about the desired outcome. For paroxysmal atrial fibrillation (pAF), I really doubt you would get a clear signal from the available data predicting onset 30-60 minutes before the event itself - there are far too many complex, stochastic factors at play, and it is unlikely to have such a long lead time. At best, you might stratify into higher risk periods of devolving into AF.

But even if you succeeded perfectly, I'm not convinced that predicting onset of AF half an hour in advance is of much use to a clinician. I'm struggling to think of how I might use this information to alter management of my patient (as an emergency physician), just because of the nuances of current AF management. I only mention this because the task as described is already a very tricky one, and I worry the resulting value added might be disproportionately small relative to the effort expended... I could be wrong though, just my two cents!