Retrospective analysis of nursing interventions using artificial intelligence multimodal emotion recognition for perioperative depression in head and neck tumors

doi:10.5498/wjp.122781

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World Journal of Psychiatry

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2220-3206

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

Copyright: ©Author(s) 2026. 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.

World J Psychiatry. Nov 19, 2026; 16(11): 122781
Published online Nov 19, 2026. doi: 10.5498/wjp.122781

Table 2 Correlation analysis of artificial intelligence multimodal emotion parameters and Hamilton Depression Rating Scale score

Variable	R value	P value
Comprehensive emotional score (point)	-0.624	< 0.001
Proportion of positive emotions	-0.592	< 0.001
EMI	0.671	< 0.001
ERS	-0.561	< 0.001
Facial modal quality score	-0.208	0.112

EMI: Emotional Mood Index; ERS: Emotional Recovery Score.

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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
URL: https://www.wjgnet.com/2220-3206/full/v16/i11/122781.htm
DOI: https://dx.doi.org/10.5498/wjp.122781

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 [DOI: 10.5498/wjp.122781]

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