Uncovering and mitigating bias in large, automated MRI analyses of brain development

Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk (1,2). However, MRI studies of youth are especially susceptible to motion and other artifacts (3,4). These artifacts may go undetected by automated quality control (QC)...

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Detalles Bibliográficos
Autores principales: Elyounssi, Safia, Kunitoki, Keiko, Clauss, Jacqueline A., Laurent, Eline, Kane, Kristina, Hughes, Dylan E., Hopkinson, Casey E., Bazer, Oren, Sussman, Rachel Freed, Doyle, Alysa E., Lee, Hang, Tervo-Clemmens, Brenden, Eryilmaz, Hamdi, Gollub, Randy L., Barch, Deanna M., Satterthwaite, Theodore D., Dowling, Kevin F., Roffman, Joshua L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002762/
https://www.ncbi.nlm.nih.gov/pubmed/36909456
http://dx.doi.org/10.1101/2023.02.28.530498

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002762/
https://www.ncbi.nlm.nih.gov/pubmed/36909456
http://dx.doi.org/10.1101/2023.02.28.530498

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