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Conference papers
Network regularization in imaging genetics improves prediction performances and model interpretability on Alzheimers's disease
Abstract : Imaging-genetics is a growing popular research avenue which aims to find genetic variants associated with quantitative phenotypes that characterize a disease. In this work, we combine structural MRI with genetic data structured by prior knowledge of interactions in a Canonical Correlation Analysis (CCA) model with graph regularization. This results in improved prediction performance and yields a more inter-pretable model.
Cited literature [16 references]
https://hal-cea.archives-ouvertes.fr/cea-02016625
Contributor : Vincent Frouin Connect in order to contact the contributor
Submitted on : Tuesday, February 12, 2019 - 5:55:55 PM
Last modification on : Saturday, June 25, 2022 - 10:35:47 PM
Long-term archiving on: : Monday, May 13, 2019 - 4:20:11 PM
Contributor : Vincent Frouin Connect in order to contact the contributor
Submitted on : Tuesday, February 12, 2019 - 5:55:55 PM
Last modification on : Saturday, June 25, 2022 - 10:35:47 PM
Long-term archiving on: : Monday, May 13, 2019 - 4:20:11 PM
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