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

Machine Learning (2025) Artificial Intelligence (2049) Longitudinal and Cohort Studies in Public Health (399) Research Instruments, Questionnaires, and Tools (722)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64592, first published .
Prediction of Spontaneous Breathing Trial Outcome in Critically Ill-Ventilated Patients Using Deep Learning: Development and Verification Study

Prediction of Spontaneous Breathing Trial Outcome in Critically Ill-Ventilated Patients Using Deep Learning: Development and Verification Study

Prediction of Spontaneous Breathing Trial Outcome in Critically Ill-Ventilated Patients Using Deep Learning: Development and Verification Study

Authors of this article:

Hui-Chiao Yang1 Author Orcid Image ;   Angelica Te-Hui Hao2, 3 Author Orcid Image ;   Shih-Chia Liu2, 4 Author Orcid Image ;   Yu-Cheng Chang5 Author Orcid Image ;   Yao-Te Tsai6 Author Orcid Image ;   Shao-Jen Weng4 Author Orcid Image ;   Ming-Cheng Chan7 Author Orcid Image ;   Chen-Yu Wang7 Author Orcid Image ;   Yeong-Yuh Xu8 Author Orcid Image
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Journals

  1. Arboleda A, Franco M, Naranjo F, Giraldo B. Electromyographic Diaphragm and Electrocardiographic Signal Analysis for Weaning Outcome Classification in Mechanically Ventilated Patients. Sensors 2025;25(19):6000 View