From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics

Autor: Andre F. Marquand, Thomas Wolfers, Barbara Franke, Christian F. Beckmann, Jan K. Buitelaar
Rok vydání: 2015
Předmět:
medicine.medical_specialty
Specific phobia
Bipolar disorder
Cognitive Neuroscience
Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13]
Neuroimaging
Major depressive disorder
Field (computer science)
Pattern Recognition
Automated
Behavioral Neuroscience
Magnetic resonance imaging
Pattern recognition
medicine
Attention deficit hyperactivity disorder
Humans
Autism spectrum disorder
Psychiatry
Social anxiety disorder
Modalities
Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7]
Post-traumatic stress disorder
business.industry
Mental Disorders
Locality
Psychiatric diagnostics
220 Statistical Imaging Neuroscience
medicine.disease
3. Good health
Biomarker (cell)
Obsessive compulsive disorder
Attention-deficit/hyperactivity disorder
Neuropsychology and Physiological Psychology
Pattern recognition (psychology)
Schizophrenia
Artificial intelligence
Psychology
business
Psychiatric disorders
Zdroj: Neuroscience and Biobehavioral Reviews, 57, pp. 328-349
Neuroscience and Biobehavioral Reviews, 57, 328-49
Neuroscience and Biobehavioral Reviews, 57, pp. 328-49
Neuroscience and Biobehavioral Reviews, 57, 328-349
ISSN: 0149-7634
Popis: Contains fulltext : 152245.pdf (Publisher’s version ) (Open Access) Psychiatric disorders are increasingly being recognised as having a biological basis, but their diagnosis is made exclusively behaviourally. A promising approach for 'biomarker' discovery has been based on pattern recognition methods applied to neuroimaging data, which could yield clinical utility in future. In this review we survey the literature on pattern recognition for making diagnostic predictions in psychiatric disorders, and evaluate progress made in translating such findings towards clinical application. We evaluate studies on many criteria, including data modalities used, the types of features extracted and algorithm applied. We identify problems common to many studies, such as a relatively small sample size and a primary focus on estimating generalisability within a single study. Furthermore, we highlight challenges that are not widely acknowledged in the field including the importance of accommodating disease prevalence, the necessity of more extensive validation using large carefully acquired samples, the need for methodological innovations to improve accuracy and to discriminate between multiple disorders simultaneously. Finally, we identify specific clinical contexts in which pattern recognition can add value in the short to medium term.
Databáze: OpenAIRE
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