Cargando…
Using Multivariate Machine Learning Methods and Structural MRI to Classify Childhood Onset Schizophrenia and Healthy Controls
Introduction: Multivariate machine learning methods can be used to classify groups of schizophrenia patients and controls using structural magnetic resonance imaging (MRI). However, machine learning methods to date have not been extended beyond classification and contemporaneously applied in a meani...
Autores principales: | Greenstein, Deanna, Malley, James D., Weisinger, Brian, Clasen, Liv, Gogtay, Nitin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3365783/ https://www.ncbi.nlm.nih.gov/pubmed/22675310 http://dx.doi.org/10.3389/fpsyt.2012.00053 |
Ejemplares similares
-
Treatment of Early Onset Schizophrenia: Recent Trends, Challenges and Future Considerations
por: Vyas, Nora S., et al.
Publicado: (2012) -
Disrupted Modularity and Local Connectivity of Brain Functional Networks in Childhood-Onset Schizophrenia
por: Alexander-Bloch, Aaron F., et al.
Publicado: (2010) -
Cortical Brain Development in Schizophrenia: Insights From Neuroimaging Studies in Childhood-Onset Schizophrenia
por: Gogtay, Nitin
Publicado: (2008) -
Differentiating Childhood-Onset Schizophrenia From Other Childhood Disorders
por: Adhikari, Samicchya, et al.
Publicado: (2022) -
Bidirectional connectivity alterations in schizophrenia: a multivariate, machine-learning approach
por: Kim, Minhoe, et al.
Publicado: (2023)