Article

Fairness-Aware Machine Learning for Heart Failure Prediction: Performance, Bias, and Clinical Deployment Insights

2025-10-19

Abstract excerpt

Heart failure (HF) prediction models using machine learning (ML) must achieve a balance between performance, fairness, and real-world clinical utility. This paper assesses the potential of ML and DL models in the context of heterogeneous databases (UCI, MIMIC) and aims to derive applicable schemes for equitable deployment in healthcare. Although the Transformer models depicted notable AUC-ROC in the UCI data (0.98...

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Literature Corpus work: 952ef3f8-1dc4-5857-ad02-111c29e47971
DOI: 10.1101/2025.10.17.25338263

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