RT Journal Article
SR Electronic
T1 Multivariate Classification of Blood Oxygen Level–Dependent fMRI Data with Diagnostic Intention: A Clinical Perspective
JF American Journal of Neuroradiology
JO Am. J. Neuroradiol.
FD American Society of Neuroradiology
SP 848
OP 855
DO 10.3174/ajnr.A3713
VO 35
IS 5
A1 Sundermann, B.
A1 Herr, D.
A1 Schwindt, W.
A1 Pfleiderer, B.
YR 2014
UL http://www.ajnr.org/content/35/5/848.abstract
AB SUMMARY: There has been a recent upsurge of reports about applications of pattern-recognition techniques from the field of machine learning to functional MR imaging data as a diagnostic tool for systemic brain disease or psychiatric disorders. Entities studied include depression, schizophrenia, attention deficit hyperactivity disorder, and neurodegenerative disorders like Alzheimer dementia. We review these recent studies which—despite the optimism from some articles—predominantly constitute explorative efforts at the proof-of-concept level. There is some evidence that, in particular, support vector machines seem to be promising. However, the field is still far from real clinical application, and much work has to be done regarding data preprocessing, model optimization, and validation. Reporting standards are proposed to facilitate future meta-analyses or systematic reviews. ADHDattention deficit hyperactivity disorderCVcross-validationLDAlinear discriminant analysisMVPAmultivariate pattern analysisSVMsupport vector machine