Article

Performance metrics for models designed to predict treatment effect

2022-06-21

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Measuring the performance of models that predict individualized treatment effect is challenging because the outcomes of two alternative treatments are inherently unobservable in one patient. The C-for-benefit was proposed to measure discriminative ability. However, measures of calibration and overall performance are still lacking. We aimed to propose metrics of calibration and...

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Literature Corpus work: fabaa1f6-7467-534d-8b5c-f82704c6eac2
DOI: 10.1101/2022.06.14.22276387

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