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Full-Text Articles in Diagnosis
Cascaded Multi-View Canonical Correlation (Camcco) For Early Diagnosis Of Alzheimer's Disease Via Fusion Of Clinical, Imaging And Omic Features, Asha Singanamalli, Haibo Wang, Anant Madabhushi, Michael Weiner, Paul Aisen, Ronald Petersen, Clifford Jack, William Jagust, John Trojanowki, Arthur Toga, Laurel Beckett, Robert Green, Andrew Saykin, John Morris, Leslie Shaw, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith Heidebrink, Charles Smith, Greg A. Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Cascaded Multi-View Canonical Correlation (Camcco) For Early Diagnosis Of Alzheimer's Disease Via Fusion Of Clinical, Imaging And Omic Features, Asha Singanamalli, Haibo Wang, Anant Madabhushi, Michael Weiner, Paul Aisen, Ronald Petersen, Clifford Jack, William Jagust, John Trojanowki, Arthur Toga, Laurel Beckett, Robert Green, Andrew Saykin, John Morris, Leslie Shaw, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith Heidebrink, Charles Smith, Greg A. Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Neurology Faculty Publications
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 limitations. Most do not simultaneously consider all diagnostic categories and provide suboptimal fused representations using the same set of modalities for prediction of all classes. In this work, we present a combined framework, cascaded multiview canonical correlation (CaMCCo), for fusion and cascaded classification that incorporates all diagnostic …
Longitudinal Measurement And Hierarchical Classification Framework For The Prediction Of Alzheimer's Disease, Meiyan Huang, Wei Yang, Qianjin Feng, Wufan Chen, Michael Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack Jr., William Jagust, John Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew Saykin, John Morris, Leslie M. Shaw, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Charles D. Smith, Greg A. Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Longitudinal Measurement And Hierarchical Classification Framework For The Prediction Of Alzheimer's Disease, Meiyan Huang, Wei Yang, Qianjin Feng, Wufan Chen, Michael Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack Jr., William Jagust, John Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew Saykin, John Morris, Leslie M. Shaw, Jeffrey Kaye, Joseph Quinn, Lisa Silbert, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Charles D. Smith, Greg A. Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad
Neurology Faculty Publications
Accurate prediction of Alzheimer’s disease (AD) is important for the early diagnosis and treatment of this condition. Mild cognitive impairment (MCI) is an early stage of AD. Therefore, patients with MCI who are at high risk of fully developing AD should be identified to accurately predict AD. However, the relationship between brain images and AD is difficult to construct because of the complex characteristics of neuroimaging data. To address this problem, we present a longitudinal measurement of MCI brain images and a hierarchical classification method for AD prediction. Longitudinal images obtained from individuals with MCI were investigated to acquire important …