Aug 2026· Journal of imaging informatics in medicine· 0 citations· 34 references
Medicine
TL;DR
The proposed GBP-SCMF provides an effective and interpretable multimodal strategy for computer-aided AD diagnosis and integrates three complementary mechanisms: generative brain-prior enhancement to inject disease-related pathological knowledge into imaging representations, self-regulated multimodal alignment to reduce modality bias and feature redundancy, and clinical-imaging collaborative fusion.
Alzheimer’s disease (AD) is a neurodegenerative disorder, and mild cognitive impairment (MCI) represents a transitional stage between AD and cognitively normal (CN) individuals. Early diagnosis is clinically important for delaying disease progression. To address the limitations of single-modal approaches and the insuff...
Xiao-Li Yang, Chen-Chen Wang, Xiao Li et al.· Biomedical engineering and p...· 0 citations
Dementia is a major and growing global health burden, with Alzheimer's disease (AD) accounting for most cases. Timely and accurate diagnosis is central to managing this burden and increasingly depends on integrating complementary clinical and imaging information. Multimodal deep learning can combine these modalities fo...
Yusuf Brima, M. Atemkeng, L. Namamula et al.· 0 citations
Alzheimer's disease (AD) is a chronic neurodegenerative disease in which early diagnosis is crucial for early intervention and the appropriate management of patients. But the patho-octical changes in early stages, such as mild cognitive impairment (MCI), have been hard to detect with traditional diagnostic methods. Thi...
Tarun Kumar· Natural Resources for Human...· 0 citations
Alzheimer’s disease (AD) is a progressive neurode-generative disorder for which early and accurate diagnosis is critical for clinical management. Effective diagnosis depends on both disease staging and continuous cognitive monitoring through the Mini-Mental State Examination (MMSE), yet most existing deep learning-base...
Minh-Toan Le, Nhu-Y Tran-Van· International Conference on...· 0 citations
Introduction Early detection of Alzheimer's disease (AD) requires models that combine brain structure changes with genetic risk, but existing methods struggle to align these different data types. Methods We present R-GenIMA, an interpretable multimodal large language model that pairs a region-of-interest vision transfo...
Kun Zhao, Si-Yuan Dai, Ying-Ying Zhang et al.· Frontiers in Radiology· 0 citations
BACKGROUND
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that severely impairs cognitive and memory functions, highlighting the importance of early and accurate diagnoses. Although deep learning (DL)-based automated diagnostic systems have demonstrated promising results, many existing methods rem...
Koyya Venkata Satya Venugopala Trinadh Reddy, Gundeboyina Srinivasalu, T. V. Rao et al.· Archives of Medical Research· 0 citations
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