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PloS one, ISSN 1932-6203, 01/2017, Volume 12, Issue 1, pp. e0169364 - e0169364
Background Previous magnetic resonance imaging (MRI) research suggests that, prior to the onset of psychosis, high risk youths already exhibit brain abnormalities similar to those present in patients with schizophrenia... 
Science & Technology - Other Topics | Multidisciplinary Sciences | Science & Technology | Cerebrum - diagnostic imaging | Humans | Male | Neural Pathways - pathology | Case-Control Studies | Psychotic Disorders - physiopathology | Hallucinations - diagnostic imaging | Auditory Cortex - physiopathology | Psychotic Disorders - diagnostic imaging | Psychotic Disorders - pathology | Female | Hallucinations - pathology | Neural Pathways - physiopathology | Cerebrum - physiopathology | Cerebrum - pathology | Child | Nerve Net - physiopathology | Auditory Cortex - diagnostic imaging | Nerve Net - diagnostic imaging | Auditory Cortex - pathology | Hallucinations - physiopathology | Nerve Net - pathology | Magnetic Resonance Imaging | Neural Pathways - diagnostic imaging | Adolescent | Brain Mapping | Complications and side effects | Schizophrenia | Psychological manifestations of general diseases | Physiological aspects | Diagnosis | Research | Auditory perception | Neuroimaging | Brain | Nuclear magnetic resonance--NMR | Mental disorders | Laboratories | Neurobiology | Psychotherapy | Psychosis | Handedness | Psychiatrists | Teenagers | Computer networks | Adolescents | Cortex (auditory) | Medical imaging | Young adults | Abnormalities | Magnetic resonance | Psychosomatic medicine | Studies | Neurology | Brain research | Magnetic resonance imaging | Neural networks | Functional morphology | Hallucinations | Psychiatry | Anomalies | Index Medicus | Nuclear magnetic resonance | NMR
Journal Article
Schizophrenia bulletin, ISSN 0586-7614, 04/2018, Volume 44, Issue 3, pp. 552 - 559
Journal Article
Journal Article
Journal Article
PloS one, ISSN 1932-6203, 01/2019, Volume 14, Issue 1, pp. e0209908 - e0209908
Journal Article
PloS one, ISSN 1932-6203, 07/2017, Volume 12, Issue 7, pp. e0179638 - e0179638
In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability... 
Science & Technology - Other Topics | Multidisciplinary Sciences | Science & Technolo