Percutaneous Coronary Intervention in Patients With Gynecological Cancer: Machine Learning-Augmented Propensity Score Mortality and Cost Analysis for 383,760 Patients.

Abstract

Authors

• Nicole Thomason
  Division of Cardiology, The University of Texas Health Sciences Center at Houston, Houston, TX, United States.
• Dominique J Monlezun
  Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
• Awad Javaid
  Department of Internal Medicine, University of Nevada Las Vegas School of Medicine, Las Vegas, NV, United States.
• Alexandru Filipescu
  Division of Cardiology, The University of Texas Health Sciences Center at Houston, Houston, TX, United States.
• Efstratios Koutroumpakis
  Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
• Fisayomi Shobayo
  Division of Cardiology, The University of Texas Health Sciences Center at Houston, Houston, TX, United States.
• Peter Kim
  Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
• Juan Lopez-Mattei
  Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
• Mehmet Cilingiroglu
  Department of Internal Medicine, University of Nevada Las Vegas School of Medicine, Las Vegas, NV, United States.
• Gloria Iliescu
  Department of Internal Medicine, The University of Texas Health Sciences Center at Houston, Houston, TX, United States.
• Kostas Marmagkiolis
  Division of Cardiovascular Disease, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
• Pedro T Ramirez
  Department of GynOnc and Reproductive Medicine, The University of Texas Health Sciences Center at Houston, Houston, TX, United States.
• Cezar Iliescu
  Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.

Keywords

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