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Joint identification of imaging and proteomics biomarkers of Alzheimer's disease using network-guided sparse learning
2014
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)
Identification of biomarkers for early detection of Alzheimer's disease (AD) is an important research topic. Prior work has shown that multimodal imaging and biomarker data could provide complementary information for prediction of cognitive or AD status. However, the relationship among multiple data modalities are often ignored or oversimplified in prior studies. To address this issue, we propose a network-guided sparse learning model to embrace the complementary information and
doi:10.1109/isbi.2014.6867958
pmid:25408822
pmcid:PMC4232946
fatcat:z532s3lmrzgwfanvfldd63gu7e