[haldujai]

So what they're doing here is using deep learning on pictures of ECGs instead of the electrical signals used by machines that provide heuristics.

The proposed use case/workflow seems to be that (somehow) someone, somewhere is using an ECG machine that doesn't provide an automatic preliminary interpretation (i.e. > 20 years old) that is (somehow) still operational and the operator doesn't know how to interpret an ECG. They would then presumably upload a picture of the ECG to a platform that can run a deep learning model on the image. This is also apparently happening in a place where a clinician is then available and echo (for confirmation, quantitative EF and etiology) as well as medications are still accessible to impact patient management/outcomes.

This reads like something done by pure CS folks who don't understand how medicine works but the authors include cardiologists.

Ignoring the glaring validity issues of a study population that only included patients who had an indication for echo, the only explanation I can see for why someone would do this is to puff up the author's h-index as this will undoubtedly be cited in several "emerging applications of AI in medicine" papers.