Machine learning-based nomogram for predicting depressive symptoms in women: A cross-sectional study in Guangdong Province, China

doi:10.5498/wjp.v15.i8.106622

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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. Aug 19, 2025; 15(8): 106622
Published online Aug 19, 2025. doi: 10.5498/wjp.v15.i8.106622

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Figure 1 The flow diagram of data processing and model building process. XGBoost: Extreme gradient boosting; SVM: Support vector machine; LightGBM: Light gradient boosting machine; AUC: Area under the curve.

Citation: Chen JM, Rao M, Wei YT, Zhou QG, Tao JL, Wang SB, Bi B. Machine learning-based nomogram for predicting depressive symptoms in women: A cross-sectional study in Guangdong Province, China. World J Psychiatry 2025; 15(8): 106622
URL: https://www.wjgnet.com/2220-3206/full/v15/i8/106622.htm
DOI: https://dx.doi.org/10.5498/wjp.v15.i8.106622

Chen JM, Rao M, Wei YT, Zhou QG, Tao JL, Wang SB, Bi B. Machine learning-based nomogram for predicting depressive symptoms in women: A cross-sectional study in Guangdong Province, China. World J Psychiatry 2025; 15(8): 106622 [PMID: 40837788 DOI: 10.5498/wjp.v15.i8.106622]

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