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Scientific Reports|August 17, 2017
Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic FeaturesAsha Singanamalli, Haibo Wang, Anant Madabhushi, et al.Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 17, 2014
Selecting features with group-sparse nonnegative supervised canonical correlation analysis: multimodal prostate cancer prognosisHaibo Wang, Asha Singanamalli, Shoshana Ginsburg, et al.IEEE Transactions on Medical Imaging|September 10, 2014
Supervised multi-view canonical correlation analysis (sMVCCA): integrating histologic and proteomic features for predicting recurrent prostate cancerGeorge Lee, Asha Singanamalli, Haibo Wang, et al.Journal of Magnetic Resonance Imaging : JMRI|June 26, 2015
Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancerAsha Singanamalli, Mirabela Rusu, Rachel E Sparks, et al.Scientific Reports|July 27, 2016
AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue FragmentsGregory Penzias, Andrew Janowczyk, Asha Singanamalli, et al.Plos One|September 1, 2018
Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findingsGregory Penzias, Asha Singanamalli, Robin Elliott, et al.Pageof 1