22 June 2026 : Clinical Research
Development and Validation of Machine-Learning-Based Prediction Models for Thyroid Diseases During Pregnancy
Guang Yang BCDEF 1, Yi Gao BCEF 1, Pengfei Liu BC 1, Jingwen Jiang BC 1, Hui Qiao ADEG 1*, Weixuan Sheng
ACDE 1
DOI: 10.12659/MSM.953235
Med Sci Monit 2026; 32:e953235
Table 1 Cross-validated performance metrics for all models.
| nr task_id | learner_id | resampling_id | iters | classif.ce |
|---|---|---|---|---|
| 1: 1 train | LR | repeated_cv | 100 | 0.4367236 |
| 1: 1 train | Bayes | repeated_cv | 100 | 0.4642220 |
| 1: 1 train | KKNN | repeated_cv | 100 | 0.1699081 |
| 1: 1 train | SVM | repeated_cv | 100 | 0.4135028 |
| 1: 1 train | NNET | repeated_cv | 100 | 0.4201979 |
| 1: 1 train | CART | repeated_cv | 100 | 0.4253256 |
| 1: 1 train | XGBoost | repeated_cv | 100 | 0.3768267 |
| 1: 1 train | RF | repeated_cv | 100 | 0.1416724 |
| Abbreviations: Bayes, Bayesian approach; CART, classification and regression tree; KNN, k-nearest neighbors; LR, logistic regression; NNET, neural network; RF, random forest; SVM, support vector machine; XGBoost, extreme gradient boosting. | ||||