Early prediction of cardiovascular events following treatments in female breast cancer patients: Application of real-world data and artificial intelligence.

Journal: Breast (Edinburgh, Scotland)
Published Date: Mar 10, 2025

Abstract

• Application of real-world data and artificial intelligence in detecting cardiotoxicity following cancer treatment. • Clinical features have been used to develop prediction models. • Important features include age, tumor size, hypertension, HbA1c, HDL, creatinine, bilirubin, BUN, ALT, and diabetes. • This study offers potential approaches for cardio-oncology clinical practice.

Authors

  • Quynh T N Nguyen
    School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei City, Taiwan; Institute of Pharmaceutical Education and Research, Binh Duong University, Binh Duong province, Viet Nam.
  • Shwu-Jiuan Lin
    School of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan.
  • Phung-Anh Nguyen
    Clinical Data Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan.
  • Phan Thanh Phuc
    International Ph.D. Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan.
  • Min-Huei Hsu
    Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei, Taiwan.
  • Chun-Yao Huang
    Division of Cardiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei City, Taiwan.
  • Chin-Sheng Hung
    Department of Surgery, Taipei Medical University Hospital, Taipei Medical University, Taipei City, Taiwan.
  • Christine Y Lu
    Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States.
  • Jason C Hsu
    International Ph.D. Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan.

Keywords

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