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

Artificial Intelligence (2197) Clinical Information and Decision Making (1957) Machine Learning (2129) Electronic Health Records (1336) Tools, Programs and Algorithms (386)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52730, first published .
Using Domain Adaptation and Inductive Transfer Learning to Improve Patient Outcome Prediction in the Intensive Care Unit: Retrospective Observational Study

Using Domain Adaptation and Inductive Transfer Learning to Improve Patient Outcome Prediction in the Intensive Care Unit: Retrospective Observational Study

Using Domain Adaptation and Inductive Transfer Learning to Improve Patient Outcome Prediction in the Intensive Care Unit: Retrospective Observational Study

Authors of this article:

Maruthi Kumar Mutnuri1, 2 Author Orcid Image ;   Henry Thomas Stelfox3, 4 Author Orcid Image ;   Nils Daniel Forkert5, 6 Author Orcid Image ;   Joon Lee1, 7, 8, 9 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

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  3. Yuan S, Guo L, Xu F. Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment. International Urology and Nephrology 2025 View
  4. Umar M, Shamim L, Musharaf I, Tabasum P, Malhotra V, Farhan K, Hidayat A, Waqas M, Anwar A, Qadri M, Reza S. The integration of generative artificial intelligence and machine learning in healthcare: Current applications and future directions. Journal of Intelligent Medicine 2025;2(4):179 View

Conference Proceedings

  1. Bhavani D, Nimmala S, Adudhodla M, Rambabu B, Reddy R, Narsimhulu P. 2025 International Conference on Sustainable Communication Networks and Application (ICSCN). Hybrid Cross-Domain Transfer Learning for Large-Scale Healthcare Analytics in Low-Resource Settings View