Prediction of Aneurysm Sac Shrinkage After Endovascular Aortic Repair Using Machine Learning-Based Decision Tree Analysis.

Journal: The Journal of surgical research
PMID: 39793306

Abstract

INTRODUCTION: A simple risk stratification model to predict aneurysm sac shrinkagein patients undergoing endovascular aortic repair (EVAR) for abdominal aortic aneurysms (AAA) was developed using machine learning-based decision tree analysis.

Authors

  • Toshiya Nishibe
    Department of Medical Informatics and Management, Hokkaido Information University, Ebetsu, Japan; Department of Cardiovascular Surgery, Tokyo Medical University, Tokyo, Japan. Electronic address: toshiyanishibe@yahoo.co.jp.
  • Tsuyoshi Iwasa
    Department of Medical Informatics and Management, Hokkaido Information University, Ebetsu, Japan.
  • Seiji Matsuda
    Faculty of Medical Informatics, Hokkaido Information University, Ebetsu, Japan.
  • Masaki Kano
    Department of Cardiovascular Surgery, Tokyo Medical University, Tokyo, Japan.
  • Shinobu Akiyama
    Department of Cardiovascular Surgery, Tokyo Medical University, Tokyo, Japan.
  • Shoji Fukuda
    Department of Cardiovascular Surgery, Tokyo Medical University, Tokyo, Japan.
  • Jun Koizumi
    Department of Radiology, Chiba University School of Medicine, Chiba, Japan.
  • Masayasu Nishibe
    Department of Surgery, Eniwa Midorino Clinic, Eniwa, Japan.
  • Alan Dardik
    Department of Surgery, Yale School of Medicine, 10 Amistad Street, Room 437, New Haven, CT 06519; The Vascular Biology and Therapeutics Program, Yale School of Medicine, New Haven, CT; Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT. Electronic address: alan.dardik@yale.edu.

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