Ann Marie Hake

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Yuetiva Deming1,*, Jian Xia1,2,*, Yefei Cai1, Jenny Lord1,3, Jorge L. Del-Aguila1, Maria Victoria Fernandez1, David Carrell1, Kathleen Black1, John Budde1, ShengMei Ma1, Benjamin Saef1, Bill Howells1, Sarah Bertelsen1, Matthew Bailey4, Perry G. Ridge4, Alzheimer’s Disease Neuroimaging Initiative (ADNI)¶, David Holtzman5,6,7,8, John C. Morris5,6,7,8, Kelly(More)
Accumulating evidence suggests that Alzheimer's disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar(More)
The introduction of mild cognitive impairment (MCI) as a diagnostic category adds to the challenges of diagnosing Alzheimer's Disease (AD). No single marker has been proven to accurately categorize patients into their respective diagnostic groups. Thus, previous studies have attempted to develop fused predictors of AD and MCI. These studies have two main(More)
Neuroimaging genetics is an emerging field that aims to identify the associations between genetic variants (e.g., single nucleotide polymorphisms (SNPs)) and quantitative traits (QTs) such as brain imaging phenotypes. In recent studies, in order to detect complex multi-SNP-multi-QT associations, bi-multivariate techniques such as various structured sparse(More)
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