Neurofind: using deep learning to make individualised inferences in brain-based disorders.

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Title: Neurofind: using deep learning to make individualised inferences in brain-based disorders.
Authors: Vieira S; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.; Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.; Center for Research in Neuropsychology and Cognitive Behavioural Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal., Baecker L; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK., Pinaya WHL; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.; Department of Biomedical Engineering, King's College London, London, UK., Garcia-Dias R; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK., Scarpazza C; Department of General Psychology, University of Padova, Padova, Italy.; IRCCS S Camillo Hospital, Venezia, Italy., Calhoun V; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, and Emory University], Atlanta, GA, USA., Mechelli A; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK. a.mechelli@kcl.ac.uk.
Source: Translational psychiatry [Transl Psychiatry] 2025 Feb 27; Vol. 15 (1), pp. 69. Date of Electronic Publication: 2025 Feb 27.
Publication Type: Journal Article
Journal Info: Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101562664 Publication Model: Electronic Cited Medium: Internet ISSN: 2158-3188 (Electronic) Linking ISSN: 21583188 NLM ISO Abbreviation: Transl Psychiatry Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2158-3188
DOI:10.1038/s41398-025-03290-x