Artificial intelligence in anesthesiology: Clinical decision support, challenges, and future directions
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Luying Huang 1 , Qirong Sun 2 , Yun Ma 2 , Hui Yang 2 *
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1 Sichuan University, West China Hospital, Department of Clinical Research Management, Chengdu, Sichuan, CHINA2 Sichuan University, West China Hospital, Department of Anesthesiology, Chengdu, Sichuan, CHINA* Corresponding Author

Abstract

Artificial intelligence (AI) is increasingly incorporated into anesthesiology as clinicians seek tools that can enhance risk assessment, strengthen intraoperative monitoring, and support timely clinical decision-making. Recent studies describe its potential to assist with preoperative evaluation, predict physiological instability, and identify postoperative complications earlier than conventional methods. These applications highlight the capacity of AI to improve consistency and situational awareness across perioperative care. However, its broader clinical use remains limited by variability in data quality, the need for transparent algorithmic behavior, and uncertainties regarding clinical validation and integration into existing workflows. Understanding both the opportunities and constraints of AI is essential for guiding its safe and meaningful incorporation into anesthesiology practice.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Review Article

J CLIN EXP INVEST, Volume 17, Issue 2, June 2026, Article No: em00857

https://doi.org/10.29333/jcei/18257

Publication date: 01 Apr 2026

Online publication date: 27 Mar 2026

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Article Downloads: 15

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