Table 2. The characteristics of machine learning–based prediction models on ART.

Study	Technique(s)	ART method	Target (outcome)	External validation
Kaufmann et al. (1997)	Artificial Neural Networks (ANN)	IVF	Pregnancy	No
Jurisica et al. (1998)	Case-based reasoning (CBR)	IVF	Pregnancy	No
Kim and Jung (2003)	Bayesian network	IVF	Pregnancy	No
Passmore et al. (2003)	C5.0 Decision Tree	IVF	Pregnancy	No
Wald et al. (2005)	4-hidden node neural network	ICSI/IVF	intrauterine pregnancy	No
Morales et al. (2008)	Bayesian classification	IVF	Embryo implantation	No
Linda et al. (2009)	Bayesian network	IVF	ongoing pregnancy	No
Chen et al. (2009)	PSO, Decision Tree J48, Naïve Bayes, Bayes Net, MLP ANN	ICSI/IVF	Pregnancy	No
Nanni et al. (2010)	SVM, NN, DT	ICSI	Pregnancy	No
Guh et al. (2011)	genetic algorithm and decision tree	ICSI	Pregnancy	No
Corani et al. (2013)	Bayesian network	IVF	Pregnancy	No
Durairaj and Ramasamy (2013)	MLP ANN	IVF	pregnancy	No
Malinowski et al. (2013)	ANN	IVF/ICSI	Pregnancy	No
Uyar et al. (2014)	NB, KNN, SVM, DT, MLP, radial basis function network	IVF/ICSI	Implantation	No
Güvenir et al. (2015)	NB and RF	IVF	clinical pregnancy	No
Chen et al. (2016)	multivariable logistic regression (LR) and multivariate adaptive regression splines (MARS)	IVF/ICSI	clinical pregnancy	No
Mirroshandel et al. (2016)	NB, SVM, MLP, IBK, KStar, Bagging (KStar), RandomCommittee, J48, RF	ICSI	1) 2PN degree prediction 2) Embryo quality prediction 3) Clinical pregnancy (Beta test) prediction	No
Hafiz et al. (2017)	SVM, RPART, RF, Adaboost, 1NN	IVF/ICSI	Implantation	No
Blank et al. (2018)	RF	IVF/ ICSI	Ongoing pregnancy	No
Hassan et al. (2018)	MLP, SVM, C4.5, CART, RF	IVF	pregnancy	No