Multivariate Classification of Blood Oxygen Level–Dependent fMRI Data with Diagnostic Intention: A Clinical Perspective

Sundermann B, Herr D, Schwindt W, Pfleiderer B

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

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.

Details zur Publikation

Jahrgang / Bandnr. / Volume35
Ausgabe / Heftnr. / Issue5
Seitenbereich848-855
StatusVeröffentlicht
Veröffentlichungsjahr2014
Sprache, in der die Publikation verfasst istEnglisch
DOI10.3174/ajnr.A3713

Autor*innen der Universität Münster

Pfleiderer, Bettina
Klinik für Radiologie Bereich Lehre & Forschung
Schwindt, Wolfram
Klinik für Radiologie Bereich Lehre & Forschung
Sundermann, Benedikt
Klinik für Radiologie Bereich Lehre & Forschung