Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment

Yixue Feng, Mansu Kim, Xiaohui Yao, Kefei Liu, Qi Long & Li Shen
Abstract Background In Alzheimer’s Diseases (AD) research, multimodal imaging analysis can unveil complementary information from multiple imaging modalities and further our understanding of the disease. One application is to discover disease subtypes using unsupervised clustering. However, existing clustering methods are often applied to input features directly, and could suffer from the curse of dimensionality with high-dimensional multimodal data. The purpose of our study is to identify multimodal imaging-driven subtypes in Mild Cognitive Impairment (MCI) participants...
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