>> In one clinical trial that used more than 900 images, IDx-DR correctly detected retinopathy about 87 percent of the time, and could correctly identify those who didn’t have the disease about 90 percent of the time.

I read that as .87 accuracy, .9 specificity (True Negative Rate). However, I can't find in the link provided in the article above the sensitivity (recall or True Positive Rate).

I'm guessing it goes a bit like this (assuming perfectly balanced classes which in reality they aren't):

           Predicted + Predicted - Total
  Actual + 378         72          450
  Actual - 45          405         450
  -------------------------------------
  Total    423         477         900
  
  Accuracy:             0.8700
  Error:                0.1300
  True Positive Rate:   0.8400
  True Negative Rate:   0.9000
  Precision:            0.8936
  Recall (TPR):         0.8400
  F-Score:              0.8660

I'm not sure how good or bad is 10% false positives and 16% false negatives are for that kind of diagnosis. The linked trial page says that 40% of diabetes patients have some degree of diabetic retinopathy (DR), that early treatment reduces vision loss "by as much as 52%" and that only some 50%-60% of people with diabetes have a yearly eye exam.

Off the top of my head, it looks like automated screening will do some good and probably more good than harm, but without knowing how doctors judge good vs harm there's no way to know for sure how useful this device will really be.