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

Artificial Intelligence (2136) Machine Learning (2079) Tools, Programs and Algorithms (378) Decision Support for Health Professionals (1543) Clinical Information and Decision Making (1919) Advanced Data Analytics in eHealth (209) Cardiology (224)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72649, first published .
A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation

Authors of this article:

Zhechuan Jin1, 2 Author Orcid Image ;   Jiale Dong1, 2 Author Orcid Image ;   Chengxiang Li1, 2 Author Orcid Image ;   Yi Jiang3 Author Orcid Image ;   Jian Yang1, 2 Author Orcid Image ;   Lei Xu4 Author Orcid Image ;   Ping Li5 Author Orcid Image ;   Zhun Xie6 Author Orcid Image ;   Yulin Li2 Author Orcid Image ;   Dongjin Wang3 Author Orcid Image ;   Zhili Ji1, 7 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Zhang Q, Jiang J. Predictive Value of Normalized Lactate Load for Patients with Acute Type A Aortic Dissection: Based on the MIMIC-IV Database. Annals of Thoracic and Cardiovascular Surgery 2025;31(1):n/a View
  2. Ayhan C, Mekhaeil M, Channawi R, Ozcan A, Akargul E, Deger A, Cayan I, Abdalla A, Chan C, Mahon R, Ayhan D, Wijns W, Sultan S, Soliman O. Applications of Artificial Intelligence as a Prognostic Tool in the Management of Acute Aortic Syndrome and Aneurysm: A Comprehensive Review. Journal of Clinical Medicine 2025;14(23):8420 View