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Table 1 Features chosen to be predictors in CHD prediction model

From: Ensemble machine learning approach for screening of coronary heart disease based on echocardiography and risk factors

2D-STE features

 

Peak systolic strain (PSS)

17 segments

Longitudinal strain

Rate of systolic strain (SSR)

17 segments

(mid-layer)

Time-to-peak (TP)

17 segments

 

Mitral valve level (MV)

3 layers (ENDO/MID/EPI)

Global strain (GS)

Papillary muscle level (PM)

3 layers

for radio

Apical level (AP)

3 layers

Global longitudinal peak strain (GLPS)

3 layers (ENDO/MID/EPI)

Peak standard deviation (PSD)

Clinic features

Age (integer)

Gender (M/F)

Hypertension (Y/N)

Diabetes (Y/N)

Hyperlipemia (Y/N)

Smoke (Y/N)

Family history (Y/N)