Creating sparser prediction models of treatment outcome in depression: a proof-of-concept study using simultaneous feature selection and hyperparameter tuning.
Background: Predicting treatment outcome in major depressive disorder (MDD) remains an essential challenge for precision psychiatry. Clinical prediction models (CPMs) based on supervised machine learning have been a promising approach for this endeavor. However, only few CPMs have focused on model s...
| Publicado en: | BMC Medical Informatics & Decision Making Vol. 22; no. 1; pp. 1 - 14 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
7/14/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |