Elucidating a magnetic resonance imaging-based neuroanatomic biomarker for psychosis: classification analysis using probabilistic brain atlas and machine learning algorithms.
|Title||Elucidating a magnetic resonance imaging-based neuroanatomic biomarker for psychosis: classification analysis using probabilistic brain atlas and machine learning algorithms.|
|Publication Type||Journal Article|
|Year of Publication||2009|
|Authors||Sun, D, van Erp TGM, Thompson PM, Bearden CE, Daley M, Kushan L, Hardt ME, Nuechterlein KH, Toga AW, Cannon TD|
|Date Published||2009 Dec 1|
|Keywords||Adult, Algorithms, Atlases as Topic, Biological Markers, Brain Mapping, cerebral cortex, Female, Humans, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Predictive Value of Tests, Psychotic Disorders, Statistics as Topic|
No objective diagnostic biomarkers or laboratory tests have yet been developed for psychotic illness. Magnetic resonance imaging (MRI) studies consistently find significant abnormalities in multiple brain structures in psychotic patients relative to healthy control subjects, but these abnormalities show substantial overlap with anatomic variation that is in the normal range and therefore nondiagnostic. Recently, efforts have been made to discriminate psychotic patients from healthy individuals using machine-learning-based pattern classification methods on MRI data.
|Alternate Journal||Biol. Psychiatry|