Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach

BACKGROUND: Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occurrence of disorders. We investigated the heterogeneous and overlapping nature of symptom endorsement in a population-based sample across three of the m...

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Detalles Bibliográficos
Autores principales: Hofman, Amy, Lier, Isabelle, Ikram, M. Arfan, van Wingerden, Marijn, Luik, Annemarie I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10044296/
https://www.ncbi.nlm.nih.gov/pubmed/36804948
http://dx.doi.org/10.1192/j.eurpsy.2023.13

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10044296/
https://www.ncbi.nlm.nih.gov/pubmed/36804948
http://dx.doi.org/10.1192/j.eurpsy.2023.13

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