Explainable soft-voting classifier for heart disease prediction using SHAP and LIME

Abstract Heart disease remains a major global health challenge, underscoring the need for predictive models that are both accurate and interpretable to support early diagnosis and clinical decision-making. Using Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations...

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Principais autores:	Samiksha Walia, Samdisha Walia, Aanshi Bhardwaj, Shruti Arora, Shubhani Aggarwal, Parveen Siwach
Format:	Artigo
Jezik:	Inglês
Izdano:	Springer 2026-02-01
Serija:	Discover Computing
Teme:	Explainable AI Machine learning algorithms SHAP LIME Clinical prediction models Feature importance
Online dostop:	https://doi.org/10.1007/s10791-026-09972-4
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