MASLD Prediction on NHANES (test)
83AUROCLogistic regression
Evaluation Results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| Logistic regressionReference=Noureddin et al., 2022, Study Population=U.S. mixed population (NHANES), Train/Validate/Test (N)=2874/ 0/ 9572025.10 | 83 | 78 | 55 | 89 | — | |
| Logistic regressionReference=Zhu et al, 2025, Study Population=Chinese hospital; external validation with U.S. mixed population (NHANES), Train/Validate/Test (N)=7003/ 2002/ 10022025.10 | 81 | 72.8 | 74.9 | 71.3 | 70.1 | |
| Ensemble of RUS boosted treesReference=Atsawarungruangkit et al, 2021, Study Population=U.S. mixed population (NHANES), Train/Validate/Test (N)=2265/ 0/ 9702025.10 | 79 | 71.1 | 72.7 | 70.6 | 56 | |
| Coarse treesReference=Atsawarungruangkit et al, 2021, Study Population=U.S. mixed population (NHANES), Train/Validate/Test (N)=2265/ 0/ 9702025.10 | 72 | 74.9 | 24.5 | 92 | 33 |