121–130 of 139 posts
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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?
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…
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…
(Breast) Cancer biopsies, with histology and outcome reports. While it isn't my research project, I've been trying to use computer vision and some naive AI to identify early breast cancer lesions in images from mouse tissue with mixed success, but it's something that can be very much accelerated with a large human dataset with outcomes. (If you work in the field and what to help/hire me with/for something like this,…
You're probably aware, but CAD is a staple of modern mammo interpretation workflows. Products like Hologic ImageChecker CAD.
Here is what you really want: Large amounts of curated/quality controlled data with ground truth that you can aggregate & share. Preferably with multiple studies and time points and/or followup. That is stated in rough order of difficulty to acquire.
Here is what you typically get fed into an learning pipeline: 1-2 orders of magnitude too small, with all kinds of noise, and no truth data(i.e. at best a bad proxy).
Hand-waving about unsupervised learning won't solve many of the really difficult problems (although it has uses, obviously). Neither will hand-waving about transfer learning. In some areas most retrospective data sets will never be really available because of consenting issues. QA is hard - the sheer variability of clinical systems in the field, not to mention protocol and practice differences, is often astonishing.
So where does that leave us? To make a real dent fast I suspect you need to focus on data availability, not problem. Ask the question:
What are the fastest path(s) to collecting large volumes of clinically representative data with some QA in place, consented for the ways we want to use it, and with real clinical truth or a decent proxy we can get at in an automated or semi-automated fashion? 1000 Bonus points if real outcome data will be available in future.
FYI, as far as I know, the Harvard Personal Genome Project is one of the only publicly available resources that has whole genome (and other) data along with health record information available for free use (CC0 licensed) [1]. Open Humans [2] and OpenSNP [3] have data along with various degrees of health record and phenotype information as well. [1] http://www.personalgenomes.org/ [2] https://www.openhumans.org/ [3] h…
Earlier 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?
It's times like this I realize just how different the rest of the world is.
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.
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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.
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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?
$150 to have a nurse put a popsicle stick on my tongue and tell me that my throat infection would probably go away on its own.
Or you could see it this way :
$150 to have a nurse put a popsicle stick on your tongue and tell you that you are very lucky to have presented today because you have a suspicious growth - which on examination turns out to be a rare form of cancer that is easily cured if detected early, but most certainly fatal otherwise
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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 tha…
I've had this discussion with my SO (who is a doctor) many times, she strongly believes the breadth+depth of knowledge required for such an AI would be too great, but perhaps as a tool for GPs, or for specific, easy ailments (i.e. telling a patient what they don't have, and if it's serious enough to raise the issue to an actual doctor).