Deep learning on electronic medical records is doomed to fail
Having worked with data from EMR systems and having worked at a large EMR software development shop myself, and now using deep learning at work quite a bit for the past few years, I'm inclined to agree.<p>This title is somewhat click bait though, because the fault is really with EMR systems and (esp) the American Healthcare system, not deep learning.<p>The entire system is designed around billing and decisions are made my hospital and insurance executives that are generally not technical. There is no incentive to clean up the system or work on a well structured open protocol for interop the same way there is in say banking. Plus, the author gives some good examples like pulse ox%, doctors and nurses are not at all concerned with or trained to record data in a way that makes sense to use programmatically. They're typically thinking only as if they're recording it for another human to read.<p>Deep learning could probably be quite useful in the medical field, but we won't know until someone comes along and disrupts the system top to bottom similar to how Tesla has done with not only manufacturing, but the sales process and shirking the dealership model. This would probably look something like Forward[1], but with a crazy amount of funding, so that insurance companies and billing codes could be ignored entirely.<p>[1]: <a href="https://goforward.com/p/home" rel="nofollow">https://goforward.com/p/home</a>