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Table 2 Prediction performance results

From: Interpretable instance disease prediction based on causal feature selection and effect analysis

Dataset

XGBOOST

With LASSO

Factual prediction network

Counterfactual prediction network

AUROC

    

 Dataset1

.574 ± 0.10

.498 ± 0.06

.681 ± 0.02

.693 ± 0.06

 Dataset2

.872 ± 0.03

.823 ± 0.61

.864 ± 0.61

.877 ± 0.03

 Dataset3

.899 ± 0.01

.862 ± 0.03

.890 ± 0.03

.911 ± 0.02

AUPRC

    

 Dataset1

.577 ± 1.02

.499 ± 0.08

.681 ± 0.04

.694 ± 0.03

 Dataset2

.878 ± 0.31

.591 ± 0.37

.861 ± 0.21

.886 ± 0.04

 Dataset3

.904 ± 0.04

.890 ± 0.02

.890 ± 0.05

.905 ± 0.02

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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