Joint Association Discovery and Diagnosis of Alzheimer's Disease by Supervised Heterogeneous Multiview Learning

@article{Zhe2014JointAD,
  title={Joint Association Discovery and Diagnosis of Alzheimer's Disease by Supervised Heterogeneous Multiview Learning},
  author={Shandian Zhe and Zenglin Xu and Yuan Qi and Peng Yu},
  journal={Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing},
  year={2014},
  pages={300-11}
}
A key step for Alzheimer's disease (AD) study is to identify associations between genetic variations and intermediate phenotypes (e.g., brain structures). At the same time, it is crucial to develop a noninvasive means for AD diagnosis. Although these two tasks-association discovery and disease diagnosis-have been treated separately by a variety of approaches, they are tightly coupled due to their common biological basis. We hypothesize that the two tasks can potentially benefit each other by a… CONTINUE READING

Similar Papers

Loading similar papers…