Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects - Schnack, Hugo G.; Nieuwenhuis, Mireille; van Haren, Neeltje E.M.; Abramovic, Lucija; Scheewe, Thomas W.; Brouwer, Rachel M.; Hulshoff Pol, Hilleke E.; Kahn, René S. (NeuroImage (Orlando, Fla.), 2014)
Keywords: Adult; Adult and adolescent clinical studies; Age; Algorithms; Artificial Intelligence; Biological and medical sciences; Bipolar disorder; Bipolar Disorder - pathology; Bipolar disorders; Brain - pathology; Classification; Diagnosis, Differential; Diffusion Tensor Imaging - methods; Female; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Independent sample; Machine learning; Male; Medical sciences; Mood disorders; MRI; NMR; Nuclear magnetic resonance; Pattern Recognition, Automated - methods; Psychiatrists; Psychology. Psychoanalysis. Psychiatry; Psychopathology. Psychiatry; Psychoses; Psychotropic drugs; Reference Values; Reproducibility of Results; Schizophrenia; Schizophrenia - pathology; Sensitivity and Specificity; Studies; Schizophrenia; Bipolar disorder; MRI; Machine learning; Classification; Psychosis; Mood disorder; Learning; Human; Acquisition process; Nuclear magnetic resonance imaging