Table 2.

Generalized studies for prediction of CVD in AI framework using input covariates.

SN	Citations	IC	DS	GT	FE	TOC	ML vs. DL	ACC	AUC
1	Gorek et al. [176] (1997)	OBBM, LBBM	30	Diagnose ED	NR	CNN	DL	80.79	0.80
2	Kellner et al. [177] (2000)	OBBM, LBBM	100	Diagnose ED	NR	CNN	DL	72.79	NA
3	Glavaš et al. [178] (2015)	OBBM, LBBM	185	Diagnose ED	NR	LR, SVN, ANN	ML	74.40	0.812
4	Chen et al. [179] (2019)	LBBM	5664	Predict ED	NR	LR, ANN, SVM, RF	HDL	76.65	0.817
5	Lingli et al. [180] (2018)	OBBM, LBBM	95	Diagnose ED	DT	SVM	ML	96.7	NR
6	Jang et al. [181] (2019)	OBBM, LBBM	187	ED drugs therapy	NR	ANN	DL	100.00	NR

SN: serial number, IC: input covariates, DS: data size, GT: ground truth, OBBM: office-based biomarker, LBBM: laboratory-base biomarker, FE: feature extraction, TOC: type of classifier, ACC (%): percentage accuracy, US: ultrasound, NR: not reported.