From Internal Validation to External Validation: An Artificial Intelligence-Based Study on Predicting Optimal Timing for Mechanical Ventilation Weaning in ICU Patients.

Journal: Studies in health technology and informatics
Published Date:

Abstract

Mechanical ventilation weaning is critical for ICU patients, as prolonged or premature use can cause adverse outcomes and resource waste. Using six years of ICU data, Chi Mei Medical Center developed two-stage AI predictive models to optimize the timing for "Trying Weaning" and "Actual Weaning." The original Chi Mei models compared to external validation at Kaohsiung Medical University Hospital demonstrated AUCs of 0.981 vs. 0.915 for "Trying Weaning" and 0.915 vs. 0.866 for "Actual Weaning." The findings demonstrate that AI-assisted tools, supported by strong external validation results, can effectively reduce ventilation time, complications, and costs. Future research will focus on model optimization and multi-center validation.

Authors

  • Chung-Feng Liu
    Department of Medical Research, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan City, 710, Taiwan.
  • Chin-Ming Chen
    Department of Recreation and Health Care Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan. chencm3383@yahoo.com.tw.
  • Ming-Ju Tsai
  • Zhih-Cherng Chen
    Division of Cardiology, Department of Internal Medicine, Chi Mei Medical Center, No. 901, Zhonghua Rd., Yongkang Dist., Tainan City 710402, Taiwan.