3 ms·
Yes, hospitals keep imaging on their PACS systems and VNAs (Vendor Neutral Archives). Large systems have millions of images, though not necessarily same body pa
by TuringNYC 5y ago
Yes, hospitals keep imaging on their PACS systems and VNAs (Vendor Neutral Archives). Large systems have millions of images, though not necessarily same body part. Very large systems have millions of the same body part alone.
Getting images is one thing. Getting labels is harder. Getting annotations on regions-of-interest is yet harder. Often the labels are stuck in unstructured data (notes.)
When I was doing my startup (https://www.dochuddle.com/ https://www.dochuddle.com/) we trained our classifier and object detector on 1.2 million images. We worked with a large sovereign on getting the images, reports, and annotations.
Just dealing with 20+ TB of images was a job in its-self...but it was indeed unreasonably effective. The success was only technical and ML success.
Even harder -- commercializing it effectively after accounting for legal/contract costs. Yet harder -- getting past conflicts of interest inherent in the US medical system. We were not successful on this front. Possibly too early (we started in 2014)
- YossarianFrPrez 5y agoInteresting; thanks for sharing. It also seems like AI/ML could be used to extract labels from unstructured notes.
- TuringNYC 5y agoYes, you can use NLP. One trick would be to use a medical vocab like https://www.snomed.org/ https://www.snomed.org/ if anyone is doing this https://en.wikipedia.org/wiki/SNOMED_CT#Semantic_tag https://en.wikipedia.org/wiki/SNOMED_CT#Semantic_tag