arXiv:2607. 07091v1 Announce Type: cross Abstract: In longitudinal Alzheimer's disease (AD) diagnosis support, clinical and imaging information is often collected at irregular visits.
By Xinyue Du, Yibo Liu, Zhenglei Zhou, Xuancheng Yao, Weimin Zhong, Qiuhui Chen
The study presents an explainable multimodal deep‑learning framework that combines a 3D CNN for T1‑weighted MRI with a feedforward network for harmonized clinical and demographic data to diagnose Alzheimer’s disease. Using 6,479 ADNI records and 1,703 OASIS‑3 records, the authors compare various model configurations on three‑way and pairwise diagnostic tasks, finding that performance and explanations vary by task, modality, fusion strategy, and cohort. SHAP and Integrated Gradients consistently highlight the MMSE score as the most influential tabular feature, while CAM‑based explanations differ across model setups and cohorts, indicating that explainability is not a stable property under cohort shift.
By Yusuf Brima, Marcellin Atemkeng, Lakshmana Rao Namamula, Antoine Vacavant
arXiv:2512. 10966v3 Announce Type: replace-cross Abstract: Accurate and early diagnosis of Alzheimer's disease (AD) is critical for effective intervention and requires integrating complementary information from multimodal neuroimaging data.
By Farica Zhuang, Shu Yang, Dinara Aliyeva, Zixuan Wen, Duy Duong-Tran, Christos Davatzikos, Tianlong Chen, Song Wang, Li Shen
arXiv:2606. 11794v1 Announce Type: cross Abstract: Neurodegenerative diseases such as Alzheimer's disease (AD) require accurate and scalable tools for assessing disease severity, yet current clinical staging remains time-intensive and prone to variability.
By Boris-Stephan Rauchmann, Jonathan Laib, Buse Ercik, Robert Perneczky, Sergio Altares-L\'opez
arXiv:2605.28397v2 Announce Type: replace
Abstract: Predicting which people with mild cognitive impairment will develop dementia matters for early treatment. Yet structural imaging models have relied...
By Sara Fin, Alireza Moayedikia, Uffe Kock Wiil, Alicia Troncoso
arXiv:2610.10648v1 Announce Type: new
Abstract: Alzheimer's disease prediction involves irregular visits, heterogeneous measurements and incomplete modalities. This study presents a multimodal multit...
By Akeem Temitope Otapo, Ghazaleh Khodabandelou, Zuheng Ming, Alice Othmani