Identification of male schizophrenia patients using brain morphology based on machine learning algorithms

doi:10.5498/wjp.v14.i6.804

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Jun 19, 2024 (publication date) through Jun 29, 2024

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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

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World J Psychiatry. Jun 19, 2024; 14(6): 804-811
Published online Jun 19, 2024. doi: 10.5498/wjp.v14.i6.804

Table 5 The performance for each structural feature

Features	AUC	Balanced accuracy, %	Sensitivity	Specificity
Surface area	0.474 (0.241-0.706)	39.50	0.789	0.000
Gray matter volume	0.553 (0.235-0.871)	56.60	0.632	0.500
Cortical thickness	0.605 (0.327-0.884)	55.70	0.947	0.167

AUC: Area under receiver operating characteristic curves.

Citation: Yu T, Pei WZ, Xu CY, Deng CC, Zhang XL. Identification of male schizophrenia patients using brain morphology based on machine learning algorithms. World J Psychiatry 2024; 14(6): 804-811
URL: https://www.wjgnet.com/2220-3206/full/v14/i6/804.htm
DOI: https://dx.doi.org/10.5498/wjp.v14.i6.804