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Investigating the predictive models of efficacy of accelerated neuronavigation-guided rTMS for suicidal depression based on multimodal large-scale brain networks

Crossref DOI link: https://doi.org/10.1016/j.ijchp.2025.100564

Published Print: 2025-01

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Pan, Fen

Li, Junle

Jin, Suhui

Hou, Chensheng

Gui, Yan

Ye, Xinyi

Zhao, Haoyang

Wang, Kaiqi

Shang, Desheng

Li, Shangda

Wang, Jinhui

Huang, Manli https://orcid.org/0000-0002-0853-0386
Funding

Funding for this research was provided by:

Social Trends Institute (2021ZD0200500)

Medical and Health Research Project of Zhejiang Province (2021KY681)

National Natural Science Foundation of China (82271562, 82472092)

Key Research and Development Program of Zhejiang Province (2023C03077)

Department of Psychiatry

Zhejiang Province Natural Science Foundation (LQ22H090005)
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Text and Data Mining valid from 2025-01-01

Text and Data Mining valid from 2025-01-01

Version of Record valid from 2025-03-26
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This article is maintained by: Elsevier

Article Title: Investigating the predictive models of efficacy of accelerated neuronavigation-guided rTMS for suicidal depression based on multimodal large-scale brain networks

Journal Title: International Journal of Clinical and Health Psychology

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.ijchp.2025.100564

Content Type: article

Copyright: © 2025 The Authors. Published by Elsevier B.V.

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