Table 2 Performance of machine learning model to identify individuals who received autoantibody testing in the validation and external test datasets

From: A machine learning model identifies patients in need of autoimmune disease testing using electronic health records

Dataset

Total n

Autoantibody tested, n (%)

AUROC (95% CI)

Sensitivity (95% CI)

Specificity (95% CI)

Accuracy (95% CI)

NPV (95% CI)

PPV (95% CI)

F1 score

Validation (BioMe cohort 1)

25,062

5792 (23)

0.93 (0.93 − 0.93)

0.90 (0.90 − 0.90)

0.87 (0.87 − 0.88)

0.89 (0.88 − 0.89)

0.90 (0.89 − 0.90)

0.88 (0.87 − 0.88)

0.89 (0.88 − 0.89)

External test (All of Us)

136,522

19,264 (14)

0.87 (0.87 − 0.88)

0.82 (0.82 − 0.83)

0.82 (0.81 − 0.82)

0.82 (0.82 − 0.82)

0.82 (0.82 − 0.82)

0.82 (0.82 − 0.82)

0.83 (0.82 − 0.82)

  1. n number, AUROC area under the receiver operating characteristic curve, NPV negative predictive value, PPV positive predictive value.