Cargando…
Accommodating Site Variation In Neuroimaging Data Using Normative And Hierarchical Bayesian Models
The potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach. However, site effects are often confounded with variables of interest in a complex manner and can bias estimates of normative models, which h...
Autores principales: | Bayer, Johanna M. M., Dinga, Richard, Kia, Seyed Mostafa, Kottaram, Akhil R., Wolfers, Thomas, Lv, Jinglei, Zalesky, Andrew, Schmaal, Lianne, Marquand, Andre |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614761/ https://www.ncbi.nlm.nih.gov/pubmed/36272672 http://dx.doi.org/10.1101/2021.02.09.430363 |
Ejemplares similares
-
Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression
por: Kia, Seyed Mostafa, et al.
Publicado: (2022) -
The Normative Modeling Framework for Computational Psychiatry
por: Rutherford, Saige, et al.
Publicado: (2022) -
Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses
por: Bayer, Johanna M. M., et al.
Publicado: (2022) -
Conceptualizing mental disorders as deviations from normative functioning
por: Marquand, Andre F., et al.
Publicado: (2019) -
Warped Bayesian Linear Regression for Normative Modelling of Big Data
por: Fraza, Charlotte J., et al.
Publicado: (2021)