(no title)
levocardia | 1 month ago
It was retrospective-only, i.e. a case series on women who were known to have breast cancer, so there were zero false negatives and zero true negatives, because all patients in the study truly had cancer.
The AI system used was a ConvNet used commercially circa 2021, which is when the data for this case series were collected.
OJFord|1 month ago
Well yes, that's the denominator for determining selectivity, which is what the headline claim is about.
Also, they need to set up their next paper:
> However, the retrospective, cancer-only design limits generalizability, highlighting the need for prospective multicenter screening trials for validation.
operatingthetan|1 month ago
Does this mean that newer AI systems would perform significantly differently?
energy123|1 month ago
The main known way to improve performance on tasks like this is getting more data.
dfee|1 month ago
f1shy|1 month ago
d0liver|1 month ago
Wouldn't this mean that AI identitied them all has having cancer?
cbarnes99|1 month ago
aurareturn|1 month ago
Edit: I have a problem with the way the title uses "AI" as a singular unchanging entity. It should really be "An AI system misses nearly...". There is no single AI and models are constantly improving - sometimes exponentially better.
boxed|1 month ago
ako|1 month ago