Modeling longitudinal imaging biomarkers with parametric Bayesian multi‐task learning

Longitudinal imaging biomarkers are invaluable for understanding the course of neurodegeneration, promising the ability to track disease progression and to detect disease earlier than cross‐sectional biomarkers. To properly realize their potential, biomarker trajectory models must be robust to both...

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Detalles Bibliográficos
Autores principales: Aksman, Leon M., Scelsi, Marzia A., Marquand, Andre F., Alexander, Daniel C., Ourselin, Sebastien, Altmann, Andre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2019
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679792/
https://www.ncbi.nlm.nih.gov/pubmed/31168892
http://dx.doi.org/10.1002/hbm.24682

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679792/
https://www.ncbi.nlm.nih.gov/pubmed/31168892
http://dx.doi.org/10.1002/hbm.24682

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