Holly Fraser discusses new findings on whether and how we can predict antidepressant response using artificial intelligence.
[read the full story...]Predicting antidepressant response using artificial intelligence
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(Brain) sex matters
Paris Lalousis reviews a recent study that looks into the differences in brain connectivity between males and females, which suggests a potential sex-based divergence in the neurobiological underpinnings of psychiatric disorders.
[read the full story...]Neuroimaging abnormalities in first-episode psychosis: clinically-relevant or not?
Joe Pierre considers a systematic review and meta-analysis on the prevalence of neuroimaging abnormalities in first-episode psychosis and the clinical relevance for service users presenting with first-episode psychosis.
[read the full story...]Improving antidepressant outcomes: what works for whom and why?
Thalia Eley and Gerome Breen explore a new systematic meta-review of predictors of antidepressant treatment outcome in depression, which looks at clinical and demographic variables, but also biomarkers including both genetic and neuroimaging data.
[read the full story...]Rise of the machine learning algorithm: the future of diagnosing schizophrenia?
Samei Huda reviews a meta-analysis of multivariate pattern recognition studies, which aims to detect neuroimaging biomarkers for schizophrenia.
[read the full story...]Advances in neuroimaging provide insights into anotomical features of the brain in people with autism
This review of literature published in the last twelve months set out to chart progress made in understanding anatomical and functional features in autism spectrum disorder (ASD). The authors searched databases for research findings in the neuroimaging of autism using a variety of Medline search terms They found that techniques such as functional magnetic resonance [read the full story…]