English(EN)Interpretable Alzheimer's Diagnosis via Multimodal Fusion of Regional Brain Experts
新AI模型通过多模态数据分析增强阿尔茨海默病诊断
作者PulseAugur 编辑部·[6 个来源]·
研究人员开发了新的多模态数据分析方法，以改善阿尔茨海默病诊断。一项研究使用 tau-PET、MRI 和认知评分的定量分析来理解生物标志物关系并识别关键的神经退行性轨迹。另一篇论文提出了一种图神经网络方法来分析立方体复制草图，将几何特征与人口统计学和神经心理学数据相结合，以实现更准确和可解释的 AD 分类。第三种方法利用专家混合框架来融合来自神经影像学和人口统计学数据的区域大脑专家，从而提供关于结构和分子成像如何有助于诊断的可解释见解。
AI
arXiv:2606.20037v1 Announce Type: new Abstract: Alzheimer's disease (AD) is an irreversible neurodegenerative disorder and a leading cause of death worldwide. Early diagnosis plays an important part especially at the Mild Cognitive Impairment stage, where timely intervention can …
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder and a leading cause of death worldwide. Early diagnosis plays an important part especially at the Mild Cognitive Impairment stage, where timely intervention can help slow its progression before it advances to …
arXiv:2606.17867v1 Announce Type: cross Abstract: Despite increasing adoption of multimodal approaches in Alzheimer's Disease (AD) research -- aimed at integrating molecular, structural, clinical, and genetic biomarkers to enhance disease characterization -- the relationships amo…
Despite increasing adoption of multimodal approaches in Alzheimer's Disease (AD) research -- aimed at integrating molecular, structural, clinical, and genetic biomarkers to enhance disease characterization -- the relationships among these modalities remain poorly understood. A sy…
arXiv:2512.16184v2 Announce Type: replace Abstract: Early and accessible detection of Alzheimer's disease (AD) remains a critical clinical challenge, and cube-copying tasks offer a simple yet informative assessment of visuospatial function. This work proposes a multimodal framewo…
arXiv cs.AI
TIER_1English(EN)·Farica Zhuang, Shu Yang, Dinara Aliyeva, Zixuan Wen, Duy Duong-Tran, Christos Davatzikos, Tianlong Chen, Song Wang, Li Shen·
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. However, conventional fusion approaches …
