Clinical-learning versus machine-learning for transdiagnostic prediction of psychosis onset in individuals at-risk

Predicting the onset of psychosis in individuals at-risk is based on robust prognostic model building methods including a priori clinical knowledge (also termed clinical-learning) to preselect predictors or machine-learning methods to select predictors automatically. To date, there is no empirical r...

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Detalles Bibliográficos
Autores principales: Fusar-Poli, Paolo, Stringer, Dominic, M. S. Durieux, Alice, Rutigliano, Grazia, Bonoldi, Ilaria, De Micheli, Andrea, Stahl, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797779/
https://www.ncbi.nlm.nih.gov/pubmed/31624229
http://dx.doi.org/10.1038/s41398-019-0600-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797779/
https://www.ncbi.nlm.nih.gov/pubmed/31624229
http://dx.doi.org/10.1038/s41398-019-0600-9

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