5 ms·
Also keep in mind that if there are positives general practitioners would refer to a specialist anyways for treatment. These specialists would be more than equi
by epmaybe 9y ago
Also keep in mind that if there are positives general practitioners would refer to a specialist anyways for treatment. These specialists would be more than equipped to detect false positives. Teleretina imaging is becoming more and more prevalent as well with eyePACS and Welch-Allyn having dedicated interpretation services, so patients wouldn't have to necessarily go somewhere for verification.
I'm more worried about the 87% accurately detected as having the disease, i.e. 13% of false negatives (FN). I don't know how many general practitioners would actually send a patient to a specialist if the device did not detect changes.
The retina seems well suited to AI approaches, though, so I'd be interested in what comes next from companies like this, DeepMind, and other researchers/organizations (look out for Lee et al over at the University of Washington)
- lallysingh 9y agoI guess the baseline for comparing the 13% would be the nonspecialist rate of the same.
- epmaybe 9y agoPerhaps, that's one way to compare non-inferiority. Few if any primary care physicians take the time to look in ones eye (don't know how to use direct ophthalmoscope, don't have other specialized fundus cameras in clinic). Given that, if this tool forces them to take more retinal photographs of all patients, maybe we could detect diabetic disease before it is usually seen. The standard practice today is that if a patient is determined to be diabetic then they get referred to an ophthalmologist visit once a year. In that case would comparing those rates of diagnosis be useful?