91–100 of 139 posts
Combined phenotype/genotype datasets. These are (with some good reason) very difficult for anyone outside the medical-research establishment to get access to, but the net result is that it creates market barriers supporting the existing big players.
Anything geospatial would be superb. Disease transmission for example.
Anonymized patient records, preferrably with information about the doctor performing the diagnosis as well. I've only been able to find small datasets of some tens of thousands of records, I would like tens of millions. You can't learn much from what amounts to one small town's medical records, in terms of finding accurate diagnoses, or identify places and situations that result in better doctors.
"Anonymized" is more like it ...
OP: You need more doctor data. Given you have surgeon [x] what are odds of a successful surgery with [x]. THIS is the guarded secret -- yet the most valuable. If you have medical data (or want to be a cofounder) please email me :ransom1538 at gmail.com -- a prototype: https://www.opendoctor.io to find out data to this very question.
What is a successful surgery? One with the least complications? No complications? Shortest recovery time? Best return to function? Best outcome for that particular patient?
It's not an easy question to answer.
So, the last startup I was a fulltime engineer at actually worked in this area. What I would suggest to be maximally useful would be to focus on physiological data: EKG/ECG, EMG, glucose, SPO2, maybe various blood work counts. All of those are data that are both well-understood and are thrown away regularly, and that if fed into a computer with modern ML methods we could maybe see some really cool stuff. I'd suggest…
I would argue these are the most important areas to target. We need tremendous reform in this area, and if we can demonstrate meaningful improvement over what we have now, maybe we can let doctors get back to actually treating patients and not spending the majority of their time checking boxes on a computer.
Lyme disease frequency, given that the CDC grossly underestimated it (and admitted to that). [1] And frequency by state, especially in the Western States where it is under-diagnosed. [1] http://www.cbsnews.com/news/cdc-lyme-disease-rates-10-times-...
Dermatology, eye conditions, blood cells, tissue, viruses, urine, saliva, everything that can allow an app to give you a first diagnose before heading to the doctor. I foresee in less than ten years we will have a doctor in our pockets. No, it won't cure us and it won't replace a doctor, but it will give us all the information we need to have a 99% certainty of our condition. -- Second batch for animals and their con…
Why do you want to have the diagnosis before seeing a physician? (I'm legitimately interested in the answer.)
In my experience, it's about 50-50 with helping versus hurting making the correct diagnosis and providing accurate treatment.
Dermatology, eye conditions, blood cells, tissue, viruses, urine, saliva, everything that can allow an app to give you a first diagnose before heading to the doctor. I foresee in less than ten years we will have a doctor in our pockets. No, it won't cure us and it won't replace a doctor, but it will give us all the information we need to have a 99% certainty of our condition. -- Second batch for animals and their con…
> everything that can allow an app to give you a first diagnose before heading to the doctor. Why do you want to have the diagnosis before seeing a physician? (I'm legitimately interested in the answer.) In my experience, it's about 50-50 with helping versus hurting making the correct diagnosis and providing accurate treatment.
Combined phenotype/genotype datasets. These are (with some good reason) very difficult for anyone outside the medical-research establishment to get access to, but the net result is that it creates market barriers supporting the existing big players.
These are quite difficult to get (and very expensive to produce) even inside the medical-research establishment. Which big players are you referring to?
I understand pharma not sharing but much of the hospital/broad/university data is produced with (at least some) public money.
Please oh please, Chronic Fatigue Syndrome. The potential for ML is absolutely huge. Some people have already collected or are working to collect genetic and other data on a large scale [1] [2] [3], so it does exist. CFS is interesting because: a) Patients' symptoms appear to fluctuate "randomly" but are actually typically a complex function of genetics, blood markers, exercise, diet, medication and other factors. b)…