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Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression
- Source :
- Lecture Notes in Computer Science ISBN: 9783642236259, MICCAI (3)
- Publication Year :
- 2011
- Publisher :
- Springer Berlin Heidelberg, 2011.
-
Abstract
- Traditional neuroimaging studies in Alzheimer’s disease (AD) typically employ independent and pairwise analyses between multimodal data, which treat imaging biomarkers, cognitive measures, and disease status as isolated units. To enhance mechanistic understanding of AD, in this paper, we conduct a new study for identifying imaging biomarkers that are associated with both cognitive measures and AD. To achieve this goal, we propose a new sparse joint classification and regression method. The imaging biomarkers identified by our method are AD-sensitive and cognition-relevant and can help reveal complex relationships among brain structure, cognition and disease status. Using the imaging and cognition data from Alzheimer’s Disease Neuroimaging Initiative database, the effectiveness of the proposed method is demonstrated by clearly improved performance on predicting both cognitive scores and disease status.
- Subjects :
- Diagnostic Imaging
Pathology
medicine.medical_specialty
Disease
Machine learning
computer.software_genre
Brain mapping
Article
Cognition
Neuroimaging
Alzheimer Disease
Image Processing, Computer-Assisted
Medical imaging
Humans
Medicine
Brain Mapping
Models, Statistical
business.industry
Regression analysis
medicine.disease
Regression Analysis
Pairwise comparison
Artificial intelligence
Alzheimer's disease
Cognition Disorders
business
computer
Algorithms
Biomarkers
Subjects
Details
- ISBN :
- 978-3-642-23625-9
- ISBNs :
- 9783642236259
- Database :
- OpenAIRE
- Journal :
- Lecture Notes in Computer Science ISBN: 9783642236259, MICCAI (3)
- Accession number :
- edsair.doi.dedup.....5fa3530938c6160b84d7f3a17c21e2ad