Machine Learning on High-Dimensional Data to Predict Bleeding Post Percutaneous Coronary Intervention.

Journal: The Journal of invasive cardiology
Published Date: May 1, 2020

Abstract

INTRODUCTION: The purpose of the current study is to determine the accuracy of machine learning in predicting bleeding outcomes post percutaneous coronary intervention (PCI) in comparison with the American College of Cardiology CathPCI bleeding risk (ACC-BR) model.

Authors

  • Corbin Rayfield
  • Pradyumna Agasthi
  • Farouk Mookadam
  • Eric H Yang
  • Nithin R Venepally
  • Harish Ramakrishna
    Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Phoenix, AZ. Electronic address: Ramakrishna.harish@mayo.edu.
  • Piotr Slomka
    Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • David R Holmes
  • Reza Arsanjani
    Department of Cardiovascular Diseases, Mayo Clinic, Scottsdale, AZ.

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