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S. Namayandeh

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Open access Sep 2026

A parsimonious internally validated model for predicting in-hospital mortality using predictors available within the first 24 h in acute myocardial infarction: evidence from the Yazd Cardiovascular Disease Registry

Accurate prediction of in-hospital mortality in patients with acute myocardial infarction (AMI) is clinically critical. However, many existing risk models are complex, rely on variables not routinely available early during hospitalization, or have limited applicability in resource-constrained settings. Therefore,...

Mohammad Jokardarabi, Hasan Khademi Zare, S. Namayandeh et al. · 0 citations
Sep 2026

Evaluating the Predictive Performance of Metabolic Biomarkers for 20- Year Incidence Diabetes in the Yazd Healthy Heart Cohort: A Machine Learning Analysis

Conventional machine learning models using baseline data are insufficient for predicting diabetes incidence over long-term horizons, and the development of dynamic models that incorporate temporal changes in variables and complex pathophysiological interactions is essential for acceptable accuracy in long-term predicti...

A. Ghadiri-anari, S. Namayandeh, M. Ahi · 0 citations

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