The technique is reported to be 85% accurate. That is, there's 15% chance of false positive. According to wikipedia (<a href="http://en.wikipedia.org/wiki/Melanoma#Epidemiology" rel="nofollow">http://en.wikipedia.org/wiki/Melanoma#Epidemiology</a>), upper bound for melanoma incidence is 20 per 100000 inhabitants. Consider that 100000 people used the technique to screen themselves. There would be 15000 of them that would got the positive test result and only 20 of them who have melanoma. Thus, for a person having the positive result the probability that he indeed has the melanoma is LESS than 0.013%. That is , the probability of that the technique is reporting B.S. is over 99.8%.<p>Influenced by recent HN post: <a href="https://www.sciencenews.org/blog/context/doctors-flunk-quiz-screening-test-math" rel="nofollow">https://www.sciencenews.org/blog/context/doctors-flunk-quiz-...</a>
Single-image analysis is never going to be that accurate unless you've got a melanoma which already is very advanced. Detecting a changing lesion is a much more effective way of spotting a potential melanoma, and can catch something much sooner than these apps, many of which have come before.<p>Disclosure: I work for Skin Analytics <a href="http://skin-analytics.com" rel="nofollow">http://skin-analytics.com</a>
Interesting. Somewhat similar to a story that was posted yesterday, <a href="https://news.ycombinator.com/item?id=7703871" rel="nofollow">https://news.ycombinator.com/item?id=7703871</a>, <a href="http://www.npr.org/blogs/health/2014/05/06/309003098/chemist-turns-software-developer-after-sons-cancer-diagnosis" rel="nofollow">http://www.npr.org/blogs/health/2014/05/06/309003098/chemist...</a>