This paper is in the following e-collection/theme issue:

Clinical engineering (5) Clinical Information and Decision Making (34) Machine Learning (1501) Pulmonology, COPD (145) New Methods (963) Development of Novel Medical Devices and Innovations for Existing Devices (83)

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

Authors of this article:

Joshua Fuller1 Author Orcid Image ;   Alexey Abramov2 Author Orcid Image ;   Dana Mullin3 Author Orcid Image ;   James Beck3 Author Orcid Image ;   Philippe Lemaitre2 Author Orcid Image ;   Elham Azizi4, 5, 6, 7 Author Orcid Image
Article Authors Cited by Tweetations (3) Metrics

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