5 ms·

“significant results” can be yielded from 76 samples, provided they all be independent, and one can practically bet that they are not. But this is a claim of a

“significant results” can be yielded from 76 samples, provided they all be independent, and one can practically bet that they are not. But this is a claim of accurate diagnosis which requires more than simple significance. The a.i. being demonstrated to simply be better than chance would be a significant result, which is obviously not a spectacular standard for diagnoses. The issue is that the meaning of “significant” is very often overrated. It means nothing more than “We are highly confident that there is a stronger effect than zero.”; — this does not mean this effect is particularly large, and most importantly, it does not mean the effect is universal.

mbreese 6y ago
From Supplemental Table S2 in the paper: Non cancer patients: 26, Cancer patients: 25 So, they only had 51 individuals in the study. Then they actually divided the patients in to 3 groups: normal, PCa with pre-DRE, and PCa with post-DRE. The cancer patients thus had 2 samples, pre and post-exam: 26 + (2*25) = 76. Given the false positive rate of PSA screening, I would imagine that including more normal samples would have been more beneficial here. The method of analysis is pretty interesting though, which is where I think the novelty is for this paper. I assume that a more thorough clinical trial is planned with better numbers. This paper looks like it is more of a validation of the device than anything else.