ArticleFrontiers in neuroscience2022
Multi-modal feature selection with anchor graph for Alzheimer's disease.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Interpretable Alzheimer's Diagnosis via Multimodal Fusion of Regional Brain Experts.Proceedings. IEEE International Conference on Healthcare Informatics · 2026Article
- Multilayer Integration of Networks Toolbox (MINT).Communications biology · 2025Article
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Authors and funding
5 authors.
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Abstract
In Alzheimer's disease, the researchers found that if the patients were treated at the early stage of the disease, it could effectively delay the development of the disease. At present, multi-modal feature selection is widely used in the early diagnosis of Alzheimer's disease. However, existing multi-modal feature selection algorithms focus on learning the internal information of multiple modalities. They ignore the relationship between modalities, the importance of each modality and the local structure in the multi-modal data. In this paper, we propose a multi-modal feature selection algorithm with anchor graph for Alzheimer's disease. Specifically, we first use the least square loss and
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