| "At Darmiyan we detect Alzheimer’s disease up to 15 years before symptoms" (original post) "At present, there is no definitive evidence to support that any particular measure is effective in preventing AD"[1]. "Now we have analyzed more than 3000 brain scans and our software’s predictions are 90% accurate." (original post) "In the United States, Alzheimer prevalence was estimated to be 1.6% in 2000 both overall and in the 65–74 age group"[2] I'm assuming the 3000 brain scans you're referring to is from individuals which progressed to Alzheimers, or at least a dataset with such individuals highly represented (if this were 3000 random individuals, at a 1.6% prevalence, that amounts to 48 individuals who eventually got Alzheimers). So according to my calculation of Bayesian probability, with a 90% sensitivity (as I'm interpreting your comment), and a 1.6% prevalence in the population, a randomly screened individual with a positive test will only actually have a 12.8% chance of getting Alzheimers. So you'll be diagnosing lots of people so that they can have an impending Alzheimer's diagnosis hanging over their head for the remainder of their life without actually being able to do anything about it, and of this cohort just over 1 in 10 people will actually end up getting Alzheimers. Please tell me you're only planning on offering this for researchers, and not actually going to try to get individuals screened? Or am i missing something about your value proposition? [1]https://en.wikipedia.org/wiki/Alzheimer%27s_disease#Prevention
[2]https://en.wikipedia.org/wiki/Alzheimer%27s_disease#Epidemiology
Edit: fixed sensitivity vs. specificity error |