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Articles Published Processes
10/29/2026 7:19:27 AM | Browse: 2 | Download: 0
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Received |
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2026-06-05 11:24 |
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Peer-Review Started |
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2026-06-05 11:24 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-06-24 10:29 |
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Revised |
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2026-07-01 10:00 |
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Publication Fee Transferred |
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2026-07-07 08:20 |
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Second Decision by Editor |
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2026-07-17 02:38 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-07-17 03:49 |
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Articles in Press |
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2026-07-17 03:49 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-10-10 07:52 |
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Publish the Manuscript Online |
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2026-10-29 07:19 |
| ISSN |
2220-3206 (online) |
| Open Access |
Open-Access: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Psychiatry |
| Manuscript Type |
Retrospective Study |
| Article Title |
Retrospective analysis of nursing interventions using artificial intelligence multimodal emotion recognition for perioperative depression in head and neck tumors
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Yan-Fang Zhu, Xiao-Lin Xuan and Yi-Qi Li |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Yi-Qi Li, Associate Chief Nurse, Department of Otolaryngology and Head and Neck Surgery, Affiliated Hospital of Jiangnan University, No. 1000 Hefeng Road, Xuelang Street, Wuxi 214100, Jiangsu Province, China. 1315940822@qq.com |
| Key Words |
Head and neck tumors; Perioperative depression; Artificial intelligence; Multimodal emotion recognition; Personalized care; Quality of life |
| Core Tip |
Artificial intelligence multimodal emotion recognition has good diagnostic efficacy. Applying it to targeted nursing for head and neck tumor patients can promptly capture perioperative depressive mood, streamline nursing response, and improve emotional status and postoperative rehabilitation. |
| Publish Date |
2026-10-29 07:19 |
| Citation |
Zhu YF, Xuan XL, Li YQ. Retrospective analysis of nursing interventions using artificial intelligence multimodal emotion recognition for perioperative depression in head and neck tumors. World J Psychiatry 2026; 16(11): 122781
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| URL |
https://www.wjgnet.com/2220-3206/full/v16/i11/122781.htm |
| DOI |
https://doi.org/10.5498/wjp.122781 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
