If you want to play with this and you're looking for a decent sample exam note, I grabbed some pieces of standard looking notes (Physical, ROS, Hand exam) and tossed them into a gist here: <a href="https://gist.github.com/molsches/32fcec2499e95b5b23bc268800e22780" rel="nofollow">https://gist.github.com/molsches/32fcec2499e95b5b23bc268800e...</a><p>Mostly impressive in how it parses the data and can find conditions and tests in the unstructured data. Handles a few things strangely, but I imagine that gets better over time as it continues to be trained.<p>I think for it to truly be useful it needs some layer of semantic data mapping to something to standards like IMO/SNOMED/LOINC/RxNorm etc but I could see that being where other companies build their "products" on top of AWS vs. AWS competing with other Healthcare ML vendors in the space.
I work in the tech healthcare industry. I wonder why they only went with (or focused on?) ML/NLP text analysis to analyze data. There is a wealth of discrete data available in EMRs (pharmacy, lab, eMAR, etc.). Yes, there is plenty of diagnosis text but that is almost always associated with ICD10 codes. The only area where I believe text analysis would be useful is documentation and microbiology data, and in many cases micro is discrete as well.
This is the beginning of the final chapter in the story about the last kind of private data becoming owned by advertising companies. The final stroke of pen writing away our privacy to another institution in the name of a better future.
Read it outside the WSJ paywall (normally need to Incognito it): <a href="https://www.facebook.com/flx/warn/?u=https%3A%2F%2Fwww.wsj.com%2Farticles%2Famazon-starts-selling-software-to-mine-patient-health-records-1543352136&h=AT1MqUWOSdF4oojXXfuXTOxtB0eaP4Bh8e2Z8E6QFuT6XqRlwyj05mLQHdldYS_Tn1xEfdsZlKGYU310Cr66ZB38GX2qe0MJj08PlJvXs_yMsj7Gw9_xJYrD8OoE" rel="nofollow">https://www.facebook.com/flx/warn/?u=https%3A%2F%2Fwww.wsj.c...</a>
"It could also be an economic benefit to the Seattle-based center, Mr. Trunnell said. The center has employed about 60 people to scan and pull essential data from records on about 500,000 cancer patients. As automation does more of the work, some employees could do other tasks."<p>or be fired