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Table 3 Area-Under-the-Curves (AUC) for the ML models with or without the biomarker data

From: Interpretable machine learning predicts cardiac resynchronization therapy responses from personalized biochemical and biomechanical features

Feature Set

Biomarker Feature Used

Train AUC

(n = 635)

Test AUC

(n = 159)

No Biomarkers

None

0.63

0.74

All Biomarkers

MMP-2, MMP9, sST-2, CRP, NT- proBNP, TIMP1, TIMP2, TIMP4, sGP130, sIL2Ra, sTNFR-II, IFNg

0.75

0.77

Biomarker Score (0,1,2,3,4)

MMP-2 (≥ 982,000 pg/mL), sST-2(≥ 23,721 pg/mL), CRP (≥ 7381 ng/mL), sTNFR-II (≥ 7,090 pg/mL)

0.75

0.78