Identifying relapse predictors in individual participant data with decision trees

BACKGROUND: Depression is a highly common and recurrent condition. Predicting who is at most risk of relapse or recurrence can inform clinical practice. Applying machine-learning methods to Individual Participant Data (IPD) can be promising to improve the accuracy of risk predictions. METHODS: Indiv...

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Detalles Bibliográficos
Autores principales: Böttcher, Lucas, Breedvelt, Josefien J. F., Warren, Fiona C., Segal, Zindel, Kuyken, Willem, Bockting, Claudi L. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644580/
https://www.ncbi.nlm.nih.gov/pubmed/37957596
http://dx.doi.org/10.1186/s12888-023-05214-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644580/
https://www.ncbi.nlm.nih.gov/pubmed/37957596
http://dx.doi.org/10.1186/s12888-023-05214-9

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