Predicting the naturalistic course in anxiety disorders using clinical and biological markers: a machine learning approach

BACKGROUND: Disease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients would enable personalized management of these patients. This study aimed to predict recovery from anxiety...

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Detalles Bibliográficos
Autores principales: Bokma, Wicher A., Zhutovsky, Paul, Giltay, Erik J., Schoevers, Robert A., Penninx, Brenda W.J.H., van Balkom, Anton L.J.M., Batelaan, Neeltje M., van Wingen, Guido A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8711102/
https://www.ncbi.nlm.nih.gov/pubmed/32524918
http://dx.doi.org/10.1017/S0033291720001658

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8711102/
https://www.ncbi.nlm.nih.gov/pubmed/32524918
http://dx.doi.org/10.1017/S0033291720001658

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