A lot of the comments here reveal not having read the fine article (which is not very long). If you look at the graphic labeled &quot;How Accurate Tests Can Be Mostly Wrong,&quot; about halfway down the displayed Web article, you will see a very carefully worked out (and realistic) example about how even a very accurate medical test can result in mostly false positive indications of a disease--all that is necessary for that, mathematically, is that there is a low base rate of the disease. Examples like this have been commonplace in books about statistical reasoning for making medical decisions for more than a decade, and I have shared links to Hacker News before that make this same point. This is something everyone needs to know (but the investors in Theranos didn&#x27;t know) to make sound decisions about how much testing to do and what to do with test results.<p>Other authors who write about this issue are cited in the article kindly submitted for our discussion. I urge everyone here to read a lot of the writings of Dr. John P.A. Ioannidis,[1] who is quoted in the article.<p>[1] <a href="https:&#x2F;&#x2F;med.stanford.edu&#x2F;profiles&#x2F;john-ioannidis?tab=publications" rel="nofollow">https:&#x2F;&#x2F;med.stanford.edu&#x2F;profiles&#x2F;john-ioannidis?tab=publica...</a>