A space that IBM is hoping to own with it's "Watson for Healthcare" initiative:
http://www-03.ibm.com/press/us/en/pressrelease/36989.wss
Agile Diagnosis (YC S11) Launches: Helping Doctors With Diagnosis
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Re: Agile Diagnosis (YC S11) Launches: Helping Doctors With Diagnosis
#22I find it fascinating that AgileDiagnosis went through YC, and then six months later through RockHealth. Would any of the founders mind commenting on how/why they chose this path?
Both incubators have been crucial in their own ways. YC has an immense experience and expertise in start-ups of every kind to draw from that helps us tackle general start-up challenges decisively. Rock Health has a deep network of health and medical partners and mentors for opportunities and challenges unique to health-tech start-ups.
In retrospect, would you have done them in that order, or done Rock Health first and YC second, or does it not matter?
I don't think anyone can touch YC for the core value proposition, but domain-specific programs (for medical, enterprise, government, ...) might make some sense, and I could see the value in something like StartX as a pre-YC while-still-in-college thing.
Re: Agile Diagnosis (YC S11) Launches: Helping Doctors With Diagnosis
#23Every time I go to the doctor with anything that isn't obvious I'm always amazed that some basic ML tools aren't part of the standard practice. Especially since the standard reaction now is "here take a bunch of expensive tests, you won't be paying for most of them out of pocket so who cares!" We've had the tools for decades now to at least say "given these symptoms, it's very likely you X, Y or possibly Z". Addition…
I found this answer on Quora, by a medical student, to be quite illuminating on why machine diagnosis isn't going to be any good, any time soon. http://www.quora.com/Why-is-machine-learning-not-more-widely...
Jae is awesome, but picked a particularly difficult case.
There are certain kinds of diagnosis which are hard for humans and easy for computers, relatively, and some which are hard for computers and easy for people. (well, more likely hard for one and impossible for the other).
Truly novel things, where you aggregate data across multiple sites, are IMO the most amazing. Or, really rare but well defined conditions; doctors, especially busy ones, have a much smaller in-memory working set than computers.
I am very excited by machine diagnosis to augment humans. I don't think it will replace humans for a long time, but making humans even 1% better saves many lives and improves quality of life (and saves money).