Development of an Artificial Intelligence-Based Image Recognition System for Time-Sequence Analysis of Tracheal Intubation.

Journal: Anesthesia and analgesia
PMID: 38381700

Abstract

BACKGROUND: Total intubation time (TIT) is an objective indicator of tracheal intubation (TI) difficulties. However, large variations in TIT because of diverse initial and end targets make it difficult to compare studies. A video laryngoscope (VLS) can capture images during the TI process. By using artificial intelligence (AI) to detect airway structures, the start and end points can be freely selected, thus eliminating the inconsistencies. Further deconstructing the process and establishing time-sequence analysis may aid in gaining further understanding of the TI process.

Authors

  • Yu-Hwa Wu
    From the Department of Anesthesia, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
  • Kun-Yi Huang
    Department of Computer Science and Information Engineering, Southern Taiwan University of Science and Technology, Tainan, Taiwan.
  • Alex Chia-Chih Tseng
    Department of Anesthesiology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.

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