Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume

The present findings demonstrated that reduced thalamic subregional volumes in the L_PuA and L_MV-re might be associated with psychotic symptoms in PBD.

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Publication Details

Journal
BMC Psychiatry
Published
2025-06-03
DOI
https://doi.org/10.1186/s12888-025-07018-5
Citations
1
Primary Topic
Bipolar Disorder and Treatment
Type
article
Field-Weighted Citation Impact
1.47

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article

Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume

Linyan Su, Rongwang Yang, Shaojia Lu, Dong Cui et al.
1 citations
BMC Psychiatry
Bipolar Disorder and Treatment
1.47
article

Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume

Linyan Su, Rongwang Yang, Shaojia Lu, Dong Cui, Kejing Zhang, Qing Jiao, Weijia Gao
article en
1 citations

Abstract

The present findings demonstrated that reduced thalamic subregional volumes in the L_PuA and L_MV-re might be associated with psychotic symptoms in PBD.

BMC PsychiatryVol. 25(1)
Central South University (CN), Children's Hospital of Zhejiang University (CN), Second Xiangya Hospital of Central South University (CN), Shandong First Medical University (CN), First Affiliated Hospital Zhejiang University (CN), Zhejiang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province
Quality Education
Openalex Percentile: Top 19%
Bipolar Disorder and Treatment
1.47
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Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume — Linyan Su, Rongwang Yang, et al. · BMC Psychiatry (2025) | TGRS Research Map | TGRS