Learning Interpretable and Robust Spatiotemporal Dynamics from fMRI for Precise Identification of Neurological Disorders

Resting-state functional magnetic resonance imaging (rs-fMRI) has significantly advanced the diagnosis of brain diseases. However, existing methods are generally limited to small, disease-specific datasets with less convincing outcomes or lack the interpretability needed to identify reliable disease...

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Veröffentlicht in:	Proceedings (IEEE International Conference on Bioinformatics and Biomedicine) S. 968 - 975
Hauptverfasser:	Li, Youhao, Huang, Yongzhi, Gao, Qingchen, Chen, Pindong, Liu, Yong, Tu, Liyun
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 03.12.2024
Schlagworte:	Autoencoders Biological system modeling Biomarkers Brain disorders Brain modeling classification Functional magnetic resonance imaging Image reconstruction Measurement Neurological diseases non-negative matrix factorization Reliability resting-state fMRI Spatiotemporal phenomena supervised variational autoencoders
ISSN:	2156-1133
Online-Zugang:	Volltext
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