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Yes you are right - the representation is biased due to the image dataset that I have used. I don't think it would be useful to match the population distributi
by sungam 1y ago
Yes you are right - the representation is biased due to the image dataset that I have used.
I don't think it would be useful to match the population distribution since the fraction of skin cancers would be tiny (less than 1:1000 of the images) so users would not learn what a skin cancer looks like, however in the next version I will make it closer to 50:50 and highlight the difference from the population distribution.
- jonahx 1y agoYes. As I said matching the population base rate wouldn't be practical, so you'd need to educate on that separately from the identification learning. Let's say I achieve a 95% on the app though. Most people would have a massively over-inflated sense of their correctness in the wild. If the actual fraction is only 1/1000 and I see a friend with a lesion I identify as concerning, then my actual success rate would be: 1*0.95 / (0.05*999 + 1*0.95) So ~1.8%, not 95%. Few people understand Bayesian updating.
- sungam 1y agoThanks for this - I need to look at this more carefully