Article

Comparative Evaluation of SHAP and LIME for Clinical Interpretability in Postoperative Cardiac Surgery Mortality Prediction Models

2025-12-10

Abstract excerpt

<title>Abstract</title> <p>Aims Despite their strong predictive performance, complex machine learning (ML) models are often criticized for their lack of interpretability, especially in high-stakes clinical settings. This study aims to compare two leading explainable artificial intelligence (XAI) methods—SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME)—when applied to...

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Literature Corpus work: f100e2b1-d09f-5596-bec8-41e3a88119d4
DOI: 10.21203/rs.3.rs-7793831/v1

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