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©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Feb 6, 2024; 12(4): 681-687
Published online Feb 6, 2024. doi: 10.12998/wjcc.v12.i4.681
Published online Feb 6, 2024. doi: 10.12998/wjcc.v12.i4.681
Postoperative accurate pain assessment of children and artificial intelligence: A medical hypothesis and planned study
Jian-Ming Yue, Qi Wang, Bin Liu, Leng Zhou, Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Author contributions: Yue JM reviewed the literature and wrote the manuscript; Wang Q reviewed the manuscript and provided some suggestions; Liu B conceived the idea for the manuscript; Zhou L is the corresponding author and coordinate the writing of the paper.
Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors contributed their efforts in this manuscript.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Leng Zhou, MD, PhD, Associate Professor, Doctor, Department of Anesthesiology, West China Hospital, Sichuan University, No. 37 Guoxue Road, Wuhou District, Chengdu 610041, Sichuan Province, China. zhoulenghx@foxmail.com
Received: October 27, 2023
Peer-review started: October 27, 2023
First decision: December 31, 2023
Revised: January 2, 2023
Accepted: January 11, 2024
Article in press: January 11, 2024
Published online: February 6, 2024
Processing time: 89 Days and 20.1 Hours
Peer-review started: October 27, 2023
First decision: December 31, 2023
Revised: January 2, 2023
Accepted: January 11, 2024
Article in press: January 11, 2024
Published online: February 6, 2024
Processing time: 89 Days and 20.1 Hours
Core Tip
Core Tip: Valid and reliable pain assessment tools in perioperative period of children remain a challenging task by far. The artificial intelligence (AI) technology has reached an unprecedented level in image processing of deep facial models, which can effectively identify and systematically analyze various features of children’s facial expression. Based on the construction of a large database of images of facial expressions in children, we aim to develop an AI tool for pain assessment in order to improve the management of perioperative pain.