Prediction of transition to psychosis from an at-risk mental state using structural neuroimaging, genetic, and environmental data.

Tavares, Vânia; Vassos, Evangelos; Marquand, Andre; Stone, James; Valli, Isabel; Barker, Gareth J; Ferreira, Hugo; Prata, Diana

Tavares, Vânia; Vassos, Evangelos; Marquand, Andre; Stone, James; Valli, Isabel; Barker, Gareth J; Ferreira, Hugo; Prata, Diana.

Afiliación

Tavares V; Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal.
Vassos E; Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.
Marquand A; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
Stone J; National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley National Health System Trust, London, United Kingdom.
Valli I; Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
Barker GJ; Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, Netherlands.
Ferreira H; Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom.
Prata D; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

Front Psychiatry ; 13: 1086038, 2022.

Article en En | MEDLINE | ID: mdl-36741573

Palabras clave

ARMS; biomarker; machine learning; prognosis; schizophrenia

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Psychiatry Año: 2022 Tipo del documento: Article País de afiliación: Portugal Pais de publicación: Suiza

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