2 ms·
> Given the retinal image of one patient who (up to 5 years) later experienced a major CV event (such as a heart attack) and the image of another patient who di
by leereeves 9y ago
> Given the retinal image of one patient who (up to 5 years) later experienced a major CV event (such as a heart attack) and the image of another patient who did not, our algorithm could pick out the patient who had the CV event 70% of the time.
To put that in perspective, in this study, a random choice would be right 50% of the time.
So this is interesting, but would it be useful diagnostic tool?
- graeham 9y agoTo be truely useful as a diagnostic in major decision-making, it needs to be 90-95%+ accurate. But unfortunately there isn't anything close to this yet. High blood pressure, for example, probably more accurate than the retinal image technique here. https://www.ncbi.nlm.nih.gov/pubmed/25632496 https://www.ncbi.nlm.nih.gov/pubmed/25632496 The major goal here would be to screen for people to go for a more advanced test, like an MRI. But even that wouldn't hit the 90-95% level of predictor.