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 5 Comparison of negative emotion recognition and nursing response efficiency between the two groups, n (%)

Indicator	Conventional care group (n = 27)	Artificial intelligence personalized care group (n = 33)	t/χ² value	P value
Negative emotion recognition rate	18 (66.67)	31 (93.94)	7.377	0.007
First identification time (hours)	18.70 ± 6.32	6.82 ± 2.95	9.607	< 0.001
Nursing response time (minutes)	42.19 ± 11.73	17.67 ± 5.42	10.707	< 0.001
Intervention matching rate	16 (59.26)	30 (90.91)	8.315	0.004
Emotional improvement rate within 24 hours	14 (51.85)	27 (81.82)	6.163	0.013

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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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