I really think having price transparency across providers for both medical treatments and for medicine would be a game changer for the industry.
Ask HN: What medical datasets do you need?
111–120 of 139 posts
Re: Ask HN: What medical datasets do you need?
#112A comprehensive listing of foods and the allergies that are associated with them (a listing of food ingredients with tags like peanuts / shellfish etc... ).
Re: Ask HN: What medical datasets do you need?
#113Earlier quoted context omitted.
So the naive method is to just remove any information such as name or birth date. However the medical data is still identifiable. So we need to alter that too. However, we did analytics, so altering it might ruin the results. So we needed to design ways to scramble the data so that it wasn't identifiable, but that in aggregate the results stayed the same.
Did you use something like Differential Privacy?
I would be very interested to know if anyone is using that in practice. It seems like a promising concept.
Re: Ask HN: What medical datasets do you need?
#114Earlier quoted context omitted.
While I think it'll happen eventually, medicine is not at all black and white. Anecdotal, but I had a suspicious mole looked at, the doctor couldn't decide, got a second opinion from their colleague, he still was only 90% sure. And that's a relatively simple example. Doctors are some of the smartest/hard working people in society, and if they can still make mistakes, medical-grade AI is a long way off.
I think you will see much less "disagreement" between AIs than between doctors. I.e., subjectivity of diagnosis can be much more easily accounted for in an algorithm than in a person...
If you train all of them on the same data, you will get similar answers. That doesn't mean that those answers will be more right than a less sure doctor.
Re: Ask HN: What medical datasets do you need?
#115Earlier quoted context omitted.
Seeing a doctor can be expensive and inconvenient (another form of expensive).
I can understand inconvenient, but expensive? Even in the US where you actually have to pay for medical stuff, it can't be more than $10 or so for a quick consultation?
Not everyone has that kind of insurance.
You also have no idea of the cost of various diagnostic actions they might take. I once had blood drawn and got charged $600 for it because the lab they chose was out of network. I didn't even know there was a cost, let alone which labs to request.
Re: Ask HN: What medical datasets do you need?
#116Dermatology is complicated. A labeled image dataset of skin conditions?
Re: Ask HN: What medical datasets do you need?
#117Any tagged data sets like CCD's with SNOMED/LOINC encoding. Basically anything that is serialized in HL7/FHIR for a large enough population longitudinally. It's the time oriented set of population data for a region, like a major health center over a period of five to ten years or better.
Yeah, you could do some great work with this data. Pre-diabetes identification springs to mind.
Re: Ask HN: What medical datasets do you need?
#118Dermatology, 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.
Maybe the fact that you know your diagnosis is not the important part. If the app can verify the diagnostic data is accurate (e.g., temperature, AI image recognition of visible indicators like rashes and pupil dilation, audio analysis of heartbeat and breathing) then it can save the provider time taking these metrics in the office. Case notes are full of "subjective temp" vs "objective temp," meaning, "what the patient reported" and "what I measured on the visit." Successfully removing this distinction would be difficult, but would save provider time and paperwork. All this info could be sent directly to the doctor for diagnosis. (Possibly with AI giving a suggestion?)
Re: Ask HN: What medical datasets do you need?
#119Dermatology, 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…
One potential problem with this - the question of liability, and who is responsible for diagnostic accuracy? In this case, for some "Lab on a Chip" device providing a patient directly with diagnostic information without the vetting of a human doctor, liability would sit with the company. IBM's Watson at MD Anderson Cancer center did not work out real well for them. In other words, using AI in the realm of medical dia…
What about the treatment side? Once you have a diagnosis, could we use AI to review the patient's medical record, compare outcomes of past patients with the same diagnosis and similar histories, and suggest adjustments of personalized treatments to optimize outcomes?
Overall, of course, you're right. Liability is the problem with my suggestion. Doctors prescribe to treat, they also prescribe to meet the legally mandated standard of care and minimize second-guessing later. Looking at each patient as a unique snowflake-- or at least, part of a thinner-sliced group-- helps with the first, but directly undercuts the second goal. Such an approach would probably need to originate outside the U.S.
Re: Ask HN: What medical datasets do you need?
#120Dermatology, 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…
While I think it'll happen eventually, medicine is not at all black and white. Anecdotal, but I had a suspicious mole looked at, the doctor couldn't decide, got a second opinion from their colleague, he still was only 90% sure. And that's a relatively simple example. Doctors are some of the smartest/hard working people in society, and if they can still make mistakes, medical-grade AI is a long way off.
I'm with you, but moles in particular are pretty difficult to identify, especially on a first visit. (One of the 5 major criteria for a melanoma diagnosis is "evolving" which, by definition, requires more than one visit to identify.) Then you have complexities like basal or squamous cell carcinomas, UV induced AK, etc.
The benefit of medical-grade "AI" (in particular, multi-layered convolution neural networks) is that, given an aggregate of information (say, if you equipped every derm and oncologist with high resolution cameras and a set of parameters to standardize each datum), a trained professional[1] would be able to use that corpus as a very useful resource (used, obviously, in conjunction with their formal training and years of medical experience).
That being said - this is a question you should really be asking those who practice medicine or are actively in research for a living. Go pick up the last years issues of Nature Methods to see what problems they're encountering, and which technological gaps[2] (if any) they may have where YC AI might be applicable.
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[1] Needless to say, this is something I'd be very reluctant to release into the populace's hands, lest you have someone whip together some node.js backend and React iOS app :: "Do I have Skin Cancer? $10 to find out!". One shudders to think what sort of hysteria might follow.
[2] You would be surprised at how technologically adept some of the members of those research teams are -- within a month of DeepMind making the headlines on our tech blogosphere, I was seeing RNN being applied to their industry.