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000153367 1001_ $$0P:(DE-HGF)0$$aJohnston, B. A.$$b0$$eCorresponding Author
000153367 245__ $$aBrainstem abnormalities in attention deficit hyperactivity disorder support high accuracy individual diagnostic classification
000153367 260__ $$aNew York, NY$$bWiley-Liss$$c2014
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000153367 520__ $$aDespite extensive research, psychiatry remains an essentially clinical and, therefore, subjective clinical discipline, with no objective biomarkers to guide clinical practice and research. Development of psychiatric biomarkers is consequently important. A promising approach involves the use of machine learning with neuroimaging, to make predictions of diagnosis and treatment response for individual patients. Herein, we describe predictions of attention deficit hyperactivity disorder (ADHD) diagnosis using structural T1 weighted brain scans obtained from 34 young males with ADHD and 34 controls and a support vector machine. We report 93% accuracy of individual subject diagnostic prediction. Importantly, automated selection of brain regions supporting prediction was used. High accuracy prediction was supported by a region of reduced white matter in the brainstem, associated with a pons volumetric reduction in ADHD, adjacent to the noradrenergic locus coeruleus and dopaminergic ventral tegmental area nuclei. Medications used to treat ADHD modify dopaminergic and noradrenergic function. The white matter brainstem finding raises the possibility of “catecholamine disconnection or dysregulation” contributing to the ADHD syndrome, ameliorated by medication
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000153367 7001_ $$0P:(DE-HGF)0$$aMwangi, B.$$b1
000153367 7001_ $$0P:(DE-HGF)0$$aMatthews, K.$$b2
000153367 7001_ $$0P:(DE-HGF)0$$aCoghill, D.$$b3
000153367 7001_ $$0P:(DE-HGF)0$$aKonrad, K.$$b4
000153367 7001_ $$0P:(DE-HGF)0$$aSteele, J. D.$$b5
000153367 773__ $$0PERI:(DE-600)1492703-2$$a10.1002/hbm.22542$$n10$$p5179–5189$$tHuman brain mapping$$v35$$x1097-0193$$y2014
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000153367 9141_ $$y2014
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