Extended Data Fig. 2: Curves of negative predictive values (NPV) as a function of threshold for various predictions using external eye images.
From: Detection of signs of disease in external photographs of the eyes via deep learning
a, poor sugar control (HbA1c ≥ 9%), b-c, elevated lipids (total cholesterol ≥ 240 mg dl-1 and triglycerides ≥ 200 mg dl-1), d, moderate-or-worse diabetic retinopathy (DR), e, diabetic macular edema (DME), f, vision-threatening DR (VTDR), and g, a positive control: cataract. This is the NPV equivalent of Extended Data Fig. 1. The curves are truncated at the extreme end (when only 1% of patients are predicted negative, confidence intervals are wide) to reduce noise and improve clarity. Shaded areas indicate 95% bootstrap confidence intervals. Empty panels indicate unavailable data in validation set C and D. (*) Baseline characteristics models for validation sets A and B include self-reported age, sex, race/ethnicity and years with diabetes and were trained on the training dataset. (+) The baseline characteristics models for validation sets C and D use self-reported age and sex and were trained directly on validation sets C and D due to large differences in patient population compared to the development set. †: prespecified primary prediction tasks.
