Difficult intubation assessment using statistical factor analysis decision tree

Hsien Chang Wang, Wei Hao Chen, Chia Chi Tseng, Yu Hsien Chiu

研究成果: Article

1 引文 斯高帕斯(Scopus)


Correct and rapid tracheal intubation is an essential anesthesia task for surgical operations. Intubation highly depends on the subjective judgment and experience of the anesthetist. This paper proposes a statistical factor analysis approach to model the preferences of expert anesthetists to enable more accurate pre-operation judgments in cases of difficult intubation. Factor analysis combined with the mutual information between factors is used to generate a robust decision tree (DT) using Bartletts node splitting criterion for better decision-making. A tablet computer application is also developed to assist judgment. Several experiments were performed to investigate judgment accuracy and learning effects. Our proposed approach outperformed both a well-known C5.0 DT and an expert opinion derived DT. Encouraging results concerning robustness and efficiency were observed for our approach.

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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