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I. Cicek

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Open access 2026

Beyond Binary Classification: A Comprehensive Survival Analysis and Calibration Assessment of the Heart Failure Clinical Records Datase

Background: The Heart Failure Clinical Records dataset (n = 299) is among the most extensively reused benchmark datasets in clinical machine learning, yet the overwhelming majority of published analyses treat patient mortality as a static binary classification target and rarely test the statistical assumptions underlyi...

I. Cicek, Z. Kucukakcali · 0 citations
Open access 2026

An Interpretable XGBoost Model for Diabetes Prediction: Nested Cross-Validation, Calibration, and SHAP Analysis

Under a leakage-controlled, unbiased evaluation, XGBoost provided moderate but trustworthy discrimination together with well-calibrated probabilities for diabetes prediction, while SHAP confirmed clinically plausible predictors.

Z. Kucukakcali, I. Cicek · 0 citations

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