Machine learning models predict PTSD severity and functional impairment: A personalized medicine approach for uncovering complex associations among heterogeneous symptom profiles.

Park, Anna H; Patel, Herry; Mirabelli, James; Eder, Stephanie J; Steyrl, David; Lueger-Schuster, Brigitte; Scharnowski, Frank; O'Connor, Charlene; Martin, Patrick; Lanius, Ruth A; McKinnon, Margaret C; Nicholson, Andrew A

Park, Anna H; Patel, Herry; Mirabelli, James; Eder, Stephanie J; Steyrl, David; Lueger-Schuster, Brigitte; Scharnowski, Frank; O'Connor, Charlene; Martin, Patrick; Lanius, Ruth A; McKinnon, Margaret C; Nicholson, Andrew A.

Afiliación

Park AH; Department of Psychology, Neuroscience & Behaviour, McMaster University.
Patel H; Department of Psychiatry and Behavioural Neurosciences, McMaster University.
Mirabelli J; Department of Psychology, Neuroscience & Behaviour, McMaster University.
Eder SJ; Department of Cognition, Emotion, and Methods in Psychology, University of Vienna.
Steyrl D; Department of Cognition, Emotion, and Methods in Psychology, University of Vienna.
Lueger-Schuster B; Department of Clinical and Health Psychology, University of Vienna.
Scharnowski F; Department of Cognition, Emotion, and Methods in Psychology, University of Vienna.
O'Connor C; Homewood Health Centre.
Martin P; School of Computing, Queen's University.
Lanius RA; Homewood Research Institute.
McKinnon MC; Homewood Research Institute.
Nicholson AA; Homewood Research Institute.

Psychol Trauma ; 2023 Nov 27.

Article en En | MEDLINE | ID: mdl-38010788

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Psychol Trauma Año: 2023 Tipo del documento: Article