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Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization

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  • Lulu Lin
  • Li Ding
  • Zhongguo Fu
  • Lijiao Zhang

Abstract

Background: To construct several prediction models for the risk of stroke in coronary artery disease (CAD) patients receiving coronary revascularization based on machine learning methods. Methods: In total, 5757 CAD patients receiving coronary revascularization admitted to ICU in Medical Information Mart for Intensive Care IV (MIMIC-IV) were included in this cohort study. All the data were randomly split into the training set (n = 4029) and testing set (n = 1728) at 7:3. Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO) regression model were applied for feature screening. Variables with Pearson correlation coefficient

Suggested Citation

  • Lulu Lin & Li Ding & Zhongguo Fu & Lijiao Zhang, 2024. "Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-22, February.
    • Handle: RePEc:plo:pone00:0296402
    DOI: 10.1371/journal.pone.0296402
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