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We've started with the most common symptoms, but are building it out more. We'll add the armpit, thanks for the suggestions!

The AI component is the fact that we train our algorithm based on clinical data from real patients (started with CDC data -- 500k at the moment and counting as people use the site).

I've had bad experiences with the WebMD symptom checker like most people I've spoken to. Try typing in "chills" and you get "Lyme disease, acne, Bubonic plague" (no joke).

WebMD makes money on advertising, so they unfortunately direct you to the pages that are going to keep you on the site for longer. You may find what you have using their symptom checker, but it is really optimized to keep you clicking.



Can you be a bit less general about your algorithm? Without giving any specifics that you may wish to keep to yourself of course. What distinguishes it from statistical methods for example?


Expert systems have a history of being used very effectively in this domain. Have you considered incorporating one?


We'd love to incorporate a DXPlain or QMR as a starting point, but the true value of this is in learning from additional use/data.




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