Development and validation of a meta-learner for combining statistical and machine learning prediction models in individuals with depression

Development and validation of a meta-learner for combining statistical and machine learning prediction models in individuals with depression

Abstract Background The debate of whether machine learning models offer advantages over standard statistical methods when making predictions is ongoing. We discuss the use of a meta-learner model combining both approaches as an alternative. Methods To illustrate the development of a meta-learner, we...

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Bibliographic Details
Main Authors: Qiang Liu, Georgia Salanti, Franco De Crescenzo, Edoardo Giuseppe Ostinelli, Zhenpeng Li, Anneka Tomlinson, Andrea Cipriani, Orestis Efthimiou
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Psychiatry
Subjects:
Depression
PHQ-9
Dropout
Machine learning
Statistical model
Online Access:https://doi.org/10.1186/s12888-022-03986-0

Internet

https://doi.org/10.1186/s12888-022-03986-0

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