Afficher la couverture 'Network regularization in imaging genetics improves prediction performances and model interpretability on Alzheimers's disease | Guigui, Nicolas' en grand format
/5

0 avis

Network regularization in imaging genetics improves prediction performances and model interpretability on Alzheimers's disease

Archive ouverte

Guigui, Nicolas | Philippe, C. | Gloaguen, A. | Karkar, S. | Guillemot, V. | Löfstedt, T. | Frouin, V.

Edité par CCSD -

International audience. 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.

Suggestions

Du même auteur

Multivariate haplotype analysis of 96 sulci opening for 15,612 UK-Biobank subjects

Archive ouverte | Karkar, S. | CCSD

International audience. Imaging genetic studies of large control cohorts such as UK Biobank enable to assess the range of normal variations in brain structures. Previous studies by our group have shown that the widt...

Receptor kinase profiles identify a rationale for multitarget kinase inhibition in immature T-ALL.

Archive ouverte | Lhermitte, L. | CCSD

International audience. Constitutively activated FLT3 signaling is common in acute myeloid leukemia, and is currently under evaluation for targeted therapy, whereas little data is available in T-cell acute lymphobla...

Optical matrix imaging applied to embryology

Archive ouverte | Barolle, Victor | CCSD

High-resolution label-free imaging of oocytes and embryos is essential for in vitro fertilization procedures. Yet conventional microscopy fails in this task because of aberrations and multiple scattering induced by refractive inde...

Chargement des enrichissements...