An exploratory application of machine learning methods to optimize prediction of responsiveness to digital interventions for eating disorder symptoms

OBJECTIVE: Digital interventions show promise to address eating disorder (ED) symptoms. However, response rates are variable, and the ability to predict responsiveness to digital interventions has been poor. We tested whether machine learning (ML) techniques can enhance outcome predictions from digi...

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Detalles Bibliográficos
Autores principales: Linardon, Jake, Fuller‐Tyszkiewicz, Matthew, Shatte, Adrian, Greenwood, Christopher J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Brief Reports
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544906/
https://www.ncbi.nlm.nih.gov/pubmed/35560256
http://dx.doi.org/10.1002/eat.23733

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544906/
https://www.ncbi.nlm.nih.gov/pubmed/35560256
http://dx.doi.org/10.1002/eat.23733

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