Cargando…
Predicting escitalopram treatment response from pre-treatment and early response resting state fMRI in a multi-site sample: A CAN-BIND-1 report
Many previous intervention studies have used functional magnetic resonance imaging (fMRI) data to predict the antidepressant response of patients with major depressive disorder (MDD); however, practical constraints have limited many of those attempts to small, single centre studies which may not ade...
Autores principales: | Harris, Jacqueline K., Hassel, Stefanie, Davis, Andrew D., Zamyadi, Mojdeh, Arnott, Stephen R., Milev, Roumen, Lam, Raymond W., Frey, Benicio N., Hall, Geoffrey B., Müller, Daniel J., Rotzinger, Susan, Kennedy, Sidney H., Strother, Stephen C., MacQueen, Glenda M., Greiner, Russell |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421454/ https://www.ncbi.nlm.nih.gov/pubmed/35908308 http://dx.doi.org/10.1016/j.nicl.2022.103120 |
Ejemplares similares
-
Reliability of a functional magnetic resonance imaging task of emotional conflict in healthy participants
por: Hassel, Stefanie, et al.
Publicado: (2019) -
Exploring brain connectivity changes in major depressive disorder using functional‐structural data fusion: A CAN‐BIND‐1 study
por: Ayyash, Sondos, et al.
Publicado: (2021) -
An investigation of cortical thickness and antidepressant response in major depressive disorder: A CAN-BIND study report
por: Suh, Jee Su, et al.
Publicado: (2020) -
Multisite Comparison of MRI Defacing Software Across Multiple Cohorts
por: Theyers, Athena E., et al.
Publicado: (2021) -
Magnetic Resonance Imaging Sequence Identification Using a Metadata Learning Approach
por: Liang, Shuai, et al.
Publicado: (2021)