arXiv:2607. 09788v1 Announce Type: cross Abstract: Alzheimer's disease (AD) is a common neurodegenerative disorder, and early diagnosis is of great significance for delaying disease progression and enabling timely intervention.
By Ni Yao, Zhenxu Wang, Danyang Sun, Chuang Han, Yanting Li, Jiaofen Nan, Fubao Zhu, Chen Zhao, Weihua Zhou
arXiv:2607. 28681v1 Announce Type: cross Abstract: Functional magnetic resonance imaging (fMRI) is a widely used technique for studying the brain.
By Yang Zhang, Xiao Zhou, Jonathan Warrell, Avram Holmes, Xuan Zhang, Mark Gerstein
arXiv:2606. 03322v1 Announce Type: cross Abstract: The graphical representation of the brain offers critical insights into diagnosing and prognosing neurodegenerative disease via relationships between regions of interest (ROIs).
By Jaeyoon Sim, Minjae Lee, Guorong Wu, Won Hwa Kim
The paper introduces Explainable Graph-theoretical Machine Learning (XGML) to build individual metabolic brain graphs from FDG-PET data and identify subgraphs predictive of multivariate Alzheimer’s disease outcomes. Using ADNI data, the best model—kernel density estimation with Hellinger distance and random forest—achieved a Pearson correlation of 0.595 across eight cognitive scores, with the highest performance on ADAS13, ADAS11, and ADASQ4. Key edges were found to be jointly but differentially predictive, indicating potential network biomarkers for cognitive decline, though external validation on OASIS3 showed weaker performance likely due to cohort differences.
By Narmina Baghirova, Duy-Thanh V\~u, Duy-Cat Can, Christelle Schneuwly Diaz, Julien Bodlet, Guillaume Blanc, Georgi Hrusanov, Bernard Ries, Oliver Y. Ch\'en
arXiv:2606. 03310v1 Announce Type: cross Abstract: Understanding complex interactions between brain regions is critical for early neurodegenerative disease classification such as Alzheimer's Disease (AD) and Parkinson's Disease (PD).
By Jaeyoon Sim, Soojin Hwang, Seunghun Baek, Guorong Wu, Won Hwa Kim
arXiv:2603. 20452v2 Announce Type: replace Abstract: Longitudinal neuroimaging is essential for modeling disease progression in Alzheimer's disease (AD), yet irregular sampling and missing visits pose substantial challenges for learning reliable temporal representations.
By Ruiying Chen, Yutong Wang, Houliang Zhou, Wei Liang, Yong Chen, Lifang He