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

Journal: JMIR medical informatics
Published Date: May 21, 2025

Abstract

BACKGROUND: Long-term ventilator-dependent patients often face problems such as decreased quality of life, increased mortality, and increased medical costs. Respiratory therapists must perform complex and time-consuming ventilator weaning assessments, which typically take 48-72 hours. Traditional disengagement methods rely on manual evaluation and are susceptible to subjectivity, human errors, and low efficiency.

Authors

  • Hui-Chiao Yang
    Department of Chest Medicine, Division of Respiratory Therapy, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Angelica Te-Hui Hao
    Department of Nursing, Hungkuang University, Taichung, Taiwan.
  • Shih-Chia Liu
    Department of Nursing, Hungkuang University, Taichung, Taiwan.
  • Yu-Cheng Chang
    Vysioneer Inc, Cambridge, MA, USA.
  • Yao-Te Tsai
    Department of Information Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
  • Shao-Jen Weng
    Department of Industrial Engineering & Enterprise Information, Tunghai University, Taiwan. Electronic address: sjweng@thu.edu.tw.
  • Ming-Cheng Chan
    Department of Critical Care Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Chen-Yu Wang
    Department of Digestive Tumor, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
  • Yeong-Yuh Xu
    Department of Artificial Intelligence and Computer Engineering, National Chin-Yi University of Technology, Taichung, Taiwan.

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