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. 2022 Sep 20;4(10):e717–e726. doi: 10.1016/S2589-7500(22)00149-2

Table 2.

Tenfold stratified cross-validation performance metrics for the training and validation cohorts in stage 1 and stage 2

Accuracy AUC Sensitivity Specificity Positive predictive value Negative predictive value
Stage 1
Training
Logistic regression 95·4% (95·0–95·5) 98·6% (98·5–98·7) 92·4% (91·6–93·3) 95·6% (95·4–96·0) 70·9% (69·4–72·2) 99·1% (99·0–99·2)
Neural network 96·4% (96·1–97·2) 99·5% (99·4–99·6) 100·0% (99·2–100·0) 96·3% (96·0–96·9) 74·7% (73·9–78·8) 100·0% (99·9–100·0)
Validation
Logistic regression 96·4% (96·1–96·8) 98·5% (98·0–98·8) 93·8% (87·5–100·0) 97·0% (95·8–97·3) 65·0% (59·3–66·7) 99·6% (99·2–100·0)
Neural network 96·4% (96·1–97·8) 98·8% (98·0–99·3) 93·8% (93·8–100·0) 97·0% (95·8–98·1) 63·6% (59·3–75·0) 99·6% (99·6–100·0)
Stage 2
Training
Logistic regression 91·4% (91·2–91·5) 97·2% (97·0–97·3) 95·1% (95·0–95·1) 86·7% (86·1–86·9) 89·8% (89·6–90·0) 93·4% (93·3–93·5)
Neural network 91·7% (91·4–91·8) 97·4% (97·3–97·4) 95·0% (95·0–95·1) 87·6% (86·9–88·0) 90·4% (90·0–90·7) 93·4% (93·4–93·5)
Validation
Logistic regression 88·6% (88·2–90·1) 96·1% (95·5–96·7) 94·6% (94·6–95·3) 80·3% (78·9–84·3) 86·1% (85·2–88·1) 92·4% (92·0–92·9)
Neural network 90·1% (89·4–90·9) 96·0% (95·6–97·2) 94·6% (94·6–94·6) 84·3% (82·5–86·1) 88·6% (87·6–89·7) 92·4% (92·2–92·5)

Data are median (IQR). AUC=area under the receiver operating characteristic curve.