Published on in Vol 9 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48497, first published .
A Deep Learning Framework for Predicting Patient Decannulation on Extracorporeal Membrane Oxygenation Devices: Development and Model Analysis Study

A Deep Learning Framework for Predicting Patient Decannulation on Extracorporeal Membrane Oxygenation Devices: Development and Model Analysis Study

A Deep Learning Framework for Predicting Patient Decannulation on Extracorporeal Membrane Oxygenation Devices: Development and Model Analysis Study

Joshua Fuller   1 , BSc ;   Alexey Abramov   2 , MD ;   Dana Mullin   3 , MS, CCP ;   James Beck   3 , MS, CCP ;   Philippe Lemaitre   2 , MD, PhD ;   Elham Azizi   4, 5, 6, 7 , PhD

1 Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, United States

2 Department of Surgery, Columbia University Irving Medical Center, New York, NY, United States

3 Clinical Perfusion, New York Presbyterian Hospital, New York, NY, United States

4 Department of Biomedical Engineering, Columbia University, New York City, NY, United States

5 Irving Institute for Cancer Dynamics, Columbia University, New York, NY, United States

6 Department of Computer Science, Columbia University, New York, NY, United States

7 Data Science Institute, Columbia University, New York, NY, United States

Corresponding Author:

  • Elham Azizi, PhD
  • Department of Biomedical Engineering
  • Columbia University
  • 500 W 120th St
  • Engineering Terrace 351
  • New York City, NY, 10027
  • United States
  • Phone: 1 (212)-851-0271
  • Email: ea2690@columbia.edu