Very interesting new project by @Andrey, built on top of spaCy and using Prodigy for custom domain-specific annotation
Med7 — an information extraction model for clinical natural language processing (built with spaCy & Prodigy)
We are about a year behind this project in building out models for suicide risk factor labeling of our clinical notes. But, we are following a similar path and have identified 7 custom entities to label in our privately held clinical notes.
In any event @Andrey, I would love to hear more details about the choices you made and the lessons you learned in your path to create Med7. The medium article is well done, so of course, it focuses on the big picture with few how-to details. I found the articles and github inspirational as I sometimes feel overwhelmed with so much to learn/do.
Speaking of needing help, I did post a note in the Consultants sticky note but it doesn't seem to get much traffic. Please let me know if you recall anyone you'd recommend for this kind of work.
Dear @sleclair0, apologise for my delayed reply. I am more than happy to share as many details as possible and help with your project. Actually, there should be (very soon) a new paper from our NLP group on using free-text electronic health records for suicide risk prediction. Please drop me an email (you can find it in our med7 pre-print, bottom of the first page).