Fig. 2.

Distribution of prognostic factors across ML algorithms (a) and classical regression-based models (b). For the 16 ML algorithms, the number of feature variables ranged from 3 to 17, with a median of 7. For the 41 any-onset pre-eclampsia classical regression models, the number of predictor variables ranged from 2 to 13, with a median of 5. In the ten studies with both ML algorithm and classical regression model, the number of feature variables ranged from 3 to 17, with a median of 8. NB: Others = alcohol consumption in the first trimester, family history of chronic heart disease, and single miscarriage