Искусственный интеллект в диагностике трудных дыхательных путей: обзор литературы. Artificial intelligence for difficult airways diagnosis: review.

Published: 22 October 2024| Version 1 | DOI: 10.17632/tm2rzbd9gn.1
Contributors:
,
,
, Kirill Dubrovin,

Description

INTRODUCTION. The development of artificial intelligence has opened up the possibility of its application in the practice of an anesthesiologist in the direction associated with the most life-threatening complications - the prediction of difficult airways. This article is about the principles of artificial intelligence and the experience of its modern application to determine the risk of difficult airways. OBJECTIVES. To review the literature to determine the role of artificial intelligence in the diagnosis of difficult airways. MATERIALS AND METHODS. A review of the literature on the international Pubmed database, the Russian-language Elibrary. The search words for English-language databases were: Artificial intelligence, deep learning, difficult airways; for Russian-language: искусственный интеллект, глубокое машинное обучение, трудные дыхательные пути. The criteria for inclusion of articles were: systematic reviews, meta-analysis, randomized clinical trials, review articles. Exclusion criteria: clinical case, dissertation, abstract, thesis, application of artificial intelligence methods in pediatric practice. RESULTS. 9 articles were received for analysis. The main methods of searching for predictors of difficult airways are based on the use of photographs of patients, the use of anthropometry and physical examination data, methods using thermal imager heat maps using gradient-weighted class activation mapping. In all the analyzed works, the effectiveness of predicting difficult airways using artificial intelligence was noted, with the exception of the Siriussawakul et al. study and related to the anthropometric characteristics of patients. CONCLUSION. Diagnostic methods based on the artificial intelligence in the practice of the anesthesiologist make it easier to work and improve the detection of patients with difficult airways. However, there are still a number of unresolved issues regarding the legal and ethical components of the application of these methods in clinical practice.

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Artificial Intelligence, Anesthesia, Difficult Airways

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