Table 2.

Multiclass in CVD vs. non-CVD using seven attributes.

SN	Attributes	Multiclass CVD	Multiclass Non-CVD
1	Ground truth types	CVE [69,70,71,72,73,76,77,78,79,81,82], HF [74], MI [75], Death [80]	AD, NC, MCI, PMCI vs. SMCI [141], Proliferation, NP [139], ADH, DCS, IC [137,138,142]
2	Covariates types for the ML design	OBBM [69,70,73,74,75,76,80,82], LBBM [69,70,73,74,75,76,80,82], CUSIP [71,72,76,77,78,79,80,81,82], MU [76]	BHI [139], OBBM [137,138,141,142], LBBM [137,138,141,142]
3	Disease Type	CVD [69,70,71,72,73,74,75,76,77,78,79,80,81,82]	Diabetes [142], Cancer (Breast, Lung, Brain) [138,139], Alzheimer’s [138,141], Retinal [137]
4	Image Modalities	ECG, CT, US [71,72,76,77,78,79,80,81,82]	EEG, MRI, CT [137,139]
5	# Classes	3–9 [69,70,71,72,73,74,75,76,77,78,79,80,81,82]	5–14 [137,138,139,141,142]
6	Architecture Type	ML [70,72,76,77,78,79,80,82], DL [71,81]	ML, rMLTFL [141]
7	Classifiers used	SVM [70,75,76,77], DT, RF, LR, NB, KNN, CNN [71,79]	RetiCAC [137], PCE, SVM, CNN, DT, LR, NB, SVM, KNN, ensemble [138,139]

SN: Serial number; CVE: Cardiovascular event; AD: Alzheimer’s; NC: Normal control; MCI: Mild Cognitive impairment; PMCI: progressive MCI; SCMI: Significant memory concern; HF: Heart failure; MI: Myocardial infraction; OBBM: Office-based biomarkers; LBBM: Laboratory-based biomarkers; CUSIP: Carotid ultrasound image phenotype; ECG: Electrocardiogram; CT: Computed tomography; US: Ultrasound; MRI: Magnetic resonance imaging; BHI: Breast histopathology images; MU: MedUse; IM: Image modalities; SVM: Support vector machine; KNN: K-nearest neighbor; DT: Decision tree; RF: Random forest; LD: Logistic regression; NB: Naive Bayesian. RetiCAC: Deep learning retinal CAC score; PCE: Pooled cohort equation; rMLTFL: robust multi-label transfer feature learning.