Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45614, first published .
Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Aaron Boussina   1 , MA ;   Gabriel Wardi   2, 3 , MD ;   Supreeth Prajwal Shashikumar   1 , DPhil ;   Atul Malhotra   3 , MD ;   Kai Zheng   4 , DPhil ;   Shamim Nemati   1 , DPhil

1 Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA, United States

2 Department of Emergency Medicine, University of California San Diego, San Diego, CA, United States

3 Division of Pulmonary, Critical Care and Sleep Medicine, University of California San Diego, San Diego, CA, United States

4 Department of Informatics, University of California, Irvine, Irvine, CA, United States

Corresponding Author:

  • Aaron Boussina, MA
  • Division of Biomedical Informatics
  • University of California, San Diego
  • 9500 Gilman Dr. MC 0990
  • La Jolla, CA, 92093
  • United States
  • Phone: 1 858-534-2230
  • Email: aboussina@health.ucsd.edu