Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence
Authors
Keywords
-
Journal
SCHIZOPHRENIA BULLETIN
Volume -, Issue -, Pages -
Publisher
Oxford University Press (OUP)
Online
2018-12-20
DOI
10.1093/schbul/sby189
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium
- (2018) Theo G.M. van Erp et al. BIOLOGICAL PSYCHIATRY
- Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach
- (2018) Adriana Miyazaki de Moura et al. PSYCHIATRY RESEARCH-NEUROIMAGING
- Will Machine Learning Enable Us to Finally Cut the Gordian Knot of Schizophrenia
- (2018) Neeraj Tandon et al. SCHIZOPHRENIA BULLETIN
- Building better biomarkers: brain models in translational neuroimaging
- (2017) Choong-Wan Woo et al. NATURE NEUROSCIENCE
- Multi-center machine learning in imaging psychiatry: A meta-model approach
- (2017) Petr Dluhoš et al. NEUROIMAGE
- Inference in the age of big data: Future perspectives on neuroscience
- (2017) Danilo Bzdok et al. NEUROIMAGE
- Cross-validation failure: Small sample sizes lead to large error bars
- (2017) Gaël Varoquaux NEUROIMAGE
- Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls
- (2017) Mohammad R. Arbabshirani et al. NEUROIMAGE
- Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications
- (2017) Sandra Vieira et al. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
- Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis
- (2017) Raymond Salvador et al. PLoS One
- Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals
- (2017) Martin Rozycki et al. SCHIZOPHRENIA BULLETIN
- Improving individual predictions: Machine learning approaches for detecting and attacking heterogeneity in schizophrenia (and other psychiatric diseases)
- (2017) Hugo G. Schnack SCHIZOPHRENIA RESEARCH
- Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study
- (2017) Julie L. Winterburn et al. SCHIZOPHRENIA RESEARCH
- Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI
- (2017) Yuan Xiao et al. SCHIZOPHRENIA RESEARCH
- Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies
- (2016) Andre F. Marquand et al. BIOLOGICAL PSYCHIATRY
- Patterns of regional gray matter loss at different stages of schizophrenia: A multisite, cross-sectional VBM study in first-episode and chronic illness
- (2016) Ulysses S. Torres et al. NeuroImage-Clinical
- Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters
- (2016) Hugo G. Schnack et al. Frontiers in Psychiatry
- Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia
- (2016) Walter H. L. Pinaya et al. Scientific Reports
- The Effect of Antipsychotic Treatment on Cortical Gray Matter Changes in Schizophrenia: Does the Class Matter? A Meta-analysis and Meta-regression of Longitudinal Magnetic Resonance Imaging Studies
- (2015) Antonio Vita et al. BIOLOGICAL PSYCHIATRY
- Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium
- (2015) T G M van Erp et al. MOLECULAR PSYCHIATRY
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Detecting Neuroimaging Biomarkers for Schizophrenia: A Meta-Analysis of Multivariate Pattern Recognition Studies
- (2015) Joseph Kambeitz et al. NEUROPSYCHOPHARMACOLOGY
- From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics
- (2015) Thomas Wolfers et al. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
- A Neuroanatomical Signature for Schizophrenia Across Different Ethnic Groups
- (2015) Qiyong Gong et al. SCHIZOPHRENIA BULLETIN
- Deep learning for neuroimaging: a validation study
- (2014) Sergey M. Plis et al. Frontiers in Neuroscience
- Towards the identification of imaging biomarkers in schizophrenia, using multivariate pattern classification at a single-subject level
- (2013) Eleni Zarogianni et al. NeuroImage-Clinical
- Genetic Risk and Outcome of Psychosis (GROUP), a multi site longitudinal cohort study focused on gene-environment interaction: objectives, sample characteristics, recruitment and assessment methods
- (2012) Nikie Korver et al. INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH
- Classification of schizophrenia patients and healthy controls from structural MRI scans in two large independent samples
- (2012) Mireille Nieuwenhuis et al. NEUROIMAGE
- FreeSurfer
- (2012) Bruce Fischl NEUROIMAGE
- Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review
- (2012) Graziella Orrù et al. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
- Distinguishing Prodromal From First-Episode Psychosis Using Neuroanatomical Single-Subject Pattern Recognition
- (2012) S. Borgwardt et al. SCHIZOPHRENIA BULLETIN
- Progressive loss of cortical gray matter in schizophrenia: a meta-analysis and meta-regression of longitudinal MRI studies
- (2012) A Vita et al. Translational Psychiatry
- Neuroanatomical abnormalities in schizophrenia: A multimodal voxelwise meta-analysis and meta-regression analysis
- (2011) Emre Bora et al. SCHIZOPHRENIA RESEARCH
- Neuroimaging predictors of transition to psychosis—A systematic review and meta-analysis
- (2010) R. Smieskova et al. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
- Neuroanatomy of vulnerability to psychosis: A voxel-based meta-analysis
- (2010) P. Fusar-Poli et al. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
- High-potency cannabis and the risk of psychosis
- (2009) Marta Di Forti et al. BRITISH JOURNAL OF PSYCHIATRY
- A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging
- (2009) Chloe Hutton et al. NEUROIMAGE
- Do antipsychotic drugs affect brain structure? A systematic and critical review of MRI findings
- (2009) S. Navari et al. PSYCHOLOGICAL MEDICINE
- Brain Anatomical Abnormalities in High-Risk Individuals, First-Episode, and Chronic Schizophrenia: An Activation Likelihood Estimation Meta-analysis of Illness Progression
- (2009) R. C. K. Chan et al. SCHIZOPHRENIA BULLETIN
- Epidemiological factors associated with treated incidence of first-episode non-affective psychosis in Cantabria: insights from the Clinical Programme on Early Phases of Psychosis
- (2008) José M. Pelayo-Terán et al. Early Intervention in Psychiatry
- Voxel-based cortical thickness measurements in MRI
- (2008) Chloe Hutton et al. NEUROIMAGE
- Machine learning classifiers and fMRI: A tutorial overview
- (2008) Francisco Pereira et al. NEUROIMAGE
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started