Table 1 Model type of the 152 models developed in the 62 included publications

Regression-based models

42 (28)

 Logistic regression

26

 Cox regression

7

 Linear regression

3

 LASSO (Logistic regression)

1

 LASSO (Cox regression)

1

 LASSO (model not specified)

3

 Best subset regression with leave-out cross-validation

1

Non-regression-based models

71 (47)

 Neural network (including deep learning)

18

 Classification tree (e.g., CART, decision tree)

28

 Support vector machine

12

 Naive Bayes

6

 K nearest neighbours

3

 Other^a

4

Ensemble models

39 (26)

 Random forest (including random survival forest)

23

 Gradient boosting machine

8

 RUSBoost - boosted random forests

1

 Bagging with J48 selected by Auto-WEKA

1

 CoxBoost - boosted Cox regression

1

 XGBoost: exTreme Gradient Boosting

1

 Gradient boosting machine and Nystroem, combined using elastic net

1

 Adaboost

1

 Bagging, method not specified

1

 Partitioning Around Medoid algorithm and complete linkage method

1

Median number of models developed per study [IQR], range

2 [1–4], 1–6