Using machine learning to predict bleeding after cardiac surgery.

Journal: European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
Published Date: Dec 1, 2023

Abstract

OBJECTIVES: The primary objective was to predict bleeding after cardiac surgery with machine learning using the data from the Australia New Zealand Society of Cardiac and Thoracic Surgeons Cardiac Surgery Database, cardiopulmonary bypass perfusion database, intensive care unit database and laboratory results.

Authors

  • Victor Hui
    Department of Anaesthesia and Pain Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia.
  • Edward Litton
    Department of Intensive Care, Fiona Stanley Hospital, Perth, WA, Australia.
  • Cyrus Edibam
    Department of Intensive Care, Fiona Stanley Hospital, Perth, WA, Australia.
  • Agneta Geldenhuys
    Department of Cardiothoracic Surgery, Fiona Stanley Hospital, Perth, WA, Australia.
  • Rebecca Hahn
    Heart Lung Research Institute of Western Australia, Perth, WA, Australia.
  • Robert Larbalestier
    Department of Cardiothoracic Surgery, Fiona Stanley Hospital, Perth, WA, Australia.
  • Brian Wright
    Information Technology, Mayo Clinic, Rochester, Minnesota, USA.
  • Warren Pavey
    Heart Lung Research Institute of Western Australia, Perth, WA, Australia.

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