Fig. 2

Graphical abstract: a geographic distribution of the studies; b freaquancy of the machine learning algorthims for each congenital heart disease; c application and accuracy of machine learning algorithms in congenital heart surgery. Abbreviations: Boosting (B), Congential heart surgery (CHS), Single ventricle physiology (SVP), Aortic reconstruction (AR), Total anomalous pulmonary venous connection (TAPVC), Light gradient boosting (LGB), Extreme gradient boosting (EGB), CatBoost (CB), Transplant free survival (TFS), Mechanical ventilator support (MVS), Length of hospital stay (LoHS), Length of intensive care stay (LoICU), Acute kidney injury (AKI), artificial neural network (ANN), Neural network (NN), Deep neural network (DNN), Gradient boosting (GB), Multilayer Perceptron (MLP), Naive Bayes (NB), Bag Decision Trees (BDT), Deep venous thrombosis (DVT), Low cardiac output syndrome (LCOS), Support vector machine (SVM), Convolutional neural network (CNN), Random forest (RF), Decision tree (DT), K-nearest neighbor (KNN), Logistic regression (LR)