2024
DOI: 10.1002/sim.10057
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Model‐agnostic explanations for survival prediction models

Krithika Suresh,
Carsten Görg,
Debashis Ghosh

Abstract: Advanced machine learning methods capable of capturing complex and nonlinear relationships can be used in biomedical research to accurately predict time‐to‐event outcomes. However, these methods have been criticized as “black boxes” that are not interpretable and thus are difficult to trust in making important clinical decisions. Explainable machine learning proposes the use of model‐agnostic explainers that can be applied to predictions from any complex model. These explainers describe how a patient's charact… Show more

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