Early recognition and disease prediction in the at-risk mental states for psychosis using neurocognitive pattern classification.
about
Revisiting the Basic Symptom Concept: Toward Translating Risk Symptoms for Psychosis into Neurobiological TargetsA Hierarchical Generative Framework of Language Processing: Linking Language Perception, Interpretation, and Production Abnormalities in SchizophreniaEndophenotypes in Schizophrenia for the Perinatal Period: Criteria for Validation.Identifying Individuals at High Risk of Psychosis: Predictive Utility of Support Vector Machine using Structural and Functional MRI Data.Using genetic, cognitive and multi-modal neuroimaging data to identify ultra-high-risk and first-episode psychosis at the individual level.Improving Prognostic Accuracy in Subjects at Clinical High Risk for Psychosis: Systematic Review of Predictive Models and Meta-analytical Sequential Testing Simulation.Neurocognitive pattern analysis reveals classificatory hierarchy of attention deficits in schizophrenia.Using clinical information to make individualized prognostic predictions in people at ultra high risk for psychosis.Biomarkers and clinical staging in psychiatryDetecting the psychosis prodrome across high-risk populations using neuroanatomical biomarkers.Reduced activation in the ventral striatum during probabilistic decision-making in patients in an at-risk mental state.Prodromal psychosis detection in a counseling center population in China: an epidemiological and clinical study.Diagnostic neuroimaging across diseases.Biomarkers for Psychiatry: The Journey from Fantasy to Fact, a Report of the 2013 CINP Think TankDisease prediction in the at-risk mental state for psychosis using neuroanatomical biomarkers: results from the FePsy study.Individualized identification of euthymic bipolar disorder using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and machine learning.Assessing the potential to use neurocognition to predict who is at risk for developing bipolar disorder: a review of the literature.Hyperactivity of caudate, parahippocampal, and prefrontal regions during working memory in never-medicated persons at clinical high-risk for psychosisProgress and Future Directions in Research on the Psychosis Prodrome: A Review for Clinicians.Distinguishing prodromal from first-episode psychosis using neuroanatomical single-subject pattern recognitionPrediction of post-surgical seizure outcome in left mesial temporal lobe epilepsy.Ten year neurocognitive trajectories in first-episode psychosisPsychosis prediction and clinical utility in familial high-risk studies: selective review, synthesis, and implications for early detection and intervention.Improvements in negative symptoms and functional outcome after a new generation cognitive remediation program: a randomized controlled trial.The psychosis high-risk state: a comprehensive state-of-the-art review.Response initiation in young adults at risk for psychosis in the Northern Finland 1986 Birth Cohort.Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters.Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting.The effect of cognitive remediation in individuals at ultra-high risk for psychosis: a systematic reviewEvaluation of the 'Jumping to conclusions' bias in different subgroups of the at-risk mental state: from cognitive basic symptoms to UHR criteria.Prediction of psychosis using neural oscillations and machine learning in neuroleptic-naïve at-risk patients.A genomic lifespan program that reorganises the young adult brain is targeted in schizophrenia.Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.Cannabis use and cognitive functions in at-risk mental state and first episode psychosis.Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals.[Personalised medicine in psychiatry and psychotherapy. A review of the current state-of-the-art in the biomarker-based early recognition of psychoses].Early cognitive basic symptoms are accompanied by neurocognitive impairment in patients with an 'at-risk mental state' for psychosis.Cognitive precursors of severe mental disorders.Detection of people at risk of developing a first psychosis: comparison of two recruitment strategies.Early Intervention and a Direction of Novel Therapeutics for the Improvement of Functional Outcomes in Schizophrenia: A Selective Review.
P2860
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P2860
Early recognition and disease prediction in the at-risk mental states for psychosis using neurocognitive pattern classification.
description
2011 nî lūn-bûn
@nan
2011 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Early recognition and disease ...... nitive pattern classification.
@ast
Early recognition and disease ...... nitive pattern classification.
@en
type
label
Early recognition and disease ...... nitive pattern classification.
@ast
Early recognition and disease ...... nitive pattern classification.
@en
prefLabel
Early recognition and disease ...... nitive pattern classification.
@ast
Early recognition and disease ...... nitive pattern classification.
@en
P2093
P2860
P50
P356
P1476
Early recognition and disease ...... nitive pattern classification.
@en
P2093
Eva M Meisenzahl
Katja Patschurek-Kliche
Nikolaos Koutsouleris
Petra Decker
P2860
P304
P356
10.1093/SCHBUL/SBR037
P407
P50
P577
2011-05-16T00:00:00Z