Multimodal MRI radiomics and deep learning for brain age prediction: age-corrected brain age gap analysis in patients with insomnia

The multimodal MRI radiomics-deep learning fusion model enables accurate brain age prediction and reveals evidence of accelerated brain aging in patients with insomnia.

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Publication Details

Journal
BioMedical Engineering OnLine
Published
2026-01-09
DOI
https://doi.org/10.1186/s12938-026-01512-x
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Multimodal MRI radiomics and deep learning for brain age prediction: age-corrected brain age gap analysis in patients with insomnia

Jiandong Guo, Jingshan Gong, Junxiong Zhao, Yongyi Li et al.
BioMedical Engineering OnLine
Functional Brain Connectivity Studies
article

Multimodal MRI radiomics and deep learning for brain age prediction: age-corrected brain age gap analysis in patients with insomnia

Jiandong Guo, Jingshan Gong, Junxiong Zhao, Yongyi Li, Yue Zhou, Shasha Zeng
article en

Abstract

The multimodal MRI radiomics-deep learning fusion model enables accurate brain age prediction and reveals evidence of accelerated brain aging in patients with insomnia.

BioMedical Engineering OnLineVol. 25(1)
Jinan University (CN), Shenzhen Luohu People's Hospital (CN), Shenzhen Second People's Hospital (CN), Fourth People's Hospital of Shenzhen (CN)
Openalex Percentile: Top 93%
Functional Brain Connectivity Studies
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