Extended Data Fig. 7: ROC curves for MI prediction using different demographic data.
From: Predicting myocardial infarction through retinal scans and minimal personal information
ROC curves for MI prediction using different demographic data: An eye clinic (that is age, gender). Accuracy: 0.71 ± 0.01, Sensitivity: 0.74 ± 0.03, Specificity: 0.73 ± 0.06, Precision: 0.68 ± 0.03, and F1 Score: 0.71 ± 0.01. ROC curves for MI prediction using demographic data that may be available at a cardiology department (that is Age, Gender, BMI, Diastolic BP, Systolic BP, HbA1c scores, Glucose, Cholesterol, Smoking and Drinking status). Accuracy: 0.72 ± 0.03, Sensitivity: 0.74 ± 0.02, Specificity: 0.70 ± 0.05, Precision: 0.70 ± 0.05, and F1 Score: 0.72 ± 0.03. The solid line represents the logistic regression, and the dotted line represents the identity line.
