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October 12, 2025Reviews in Cardiovascular MedicineOpen Access

Development and Validation of an Explainable Prediction Model to Assess the Risk of Coronary Artery Disease in Young and Middle-Aged Individuals

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Authors

HSHaolin ShiSZShanshan ZhaoYWYingshuai Wang

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Overview

This model evaluates coronary artery disease risk in young individuals, suggesting improved screening using blood tests and questionnaires.

Key Points

  • The predictive model identified a high-risk group for coronary artery disease, improving early detection efforts.
  • Using data from 709 patients with coronary artery disease, LightGBM achieved an area under the curve of 0.93.
  • Feature selection involved three iterations leading to 26 pertinent features linked to hypertension and coronary artery health.
  • Employing SHAP improved the interpretability of model predictions, offering insights into individual feature contributions.

Cite This Study

Shi et al. (2025) studied this question.

synapsesocial.com/papers/68ec1be02b8fa9b2b78ad0b1https://doi.org/10.31083/rcm39006
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  1. 1Development and validation of a clinical prediction model for detecting coronary heart disease in middle-aged and elderly people: a diagnostic study2023 · 15 citations
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  5. 5Accurate Prediction of Coronary Heart Disease for Patients With Hypertension From Electronic Health Records With Big Data and Machine-Learning Methods: Model Development and Performance Evaluation (Preprint)2019