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

Abstract:: A meta-learner approach may effectively combine multiple prediction models. Choosing between statistical and machine learning models may not be necessary in practice.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Liu, Q., Salanti, G., De Crescenzo, F., Ostinelli, E. G., Li, Z., Tomlinson, A., Cipriani, A., & Efthimiou, O. (2022). Development and validation of a meta-learner for combining statistical and machine learning prediction models in individuals with depression. BMC Psychiatry, 22(1), 337–337.

MLA Style

Liu, Q, et al. “Development and Validation of a Meta-Learner for Combining Statistical and Machine Learning Prediction Models in Individuals with Depression.” BMC Psychiatry, vol. 22, no. 1, 2022, pp. 337–37.

Chicago Style

Liu, Q, G Salanti, F De Crescenzo, et al. 2022. “Development and Validation of a Meta-Learner for Combining Statistical and Machine Learning Prediction Models in Individuals with Depression.” BMC Psychiatry 22 (1): 337–37.
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Files:: Liu_et_al_2022_Development_and_validation.pdf

(Preview, Version of record, pdf, 1010.0KB, Terms of use)

Publisher copy:: 10.1186/s12888-022-03986-0

Authors

+ Liu, Q More by this author

Institution:: University of Oxford
Role:: Author
ORCID:: 0000-0001-7531-4459

+ Salanti, G More by this author

Role:: Author
ORCID:: 0000-0002-3830-8508

+ De Crescenzo, F More by this author

Institution:: University of Oxford
Role:: Author
ORCID:: 0000-0002-2478-7763

+ Ostinelli, EG More by this author

Institution:: University of Oxford
Role:: Author
ORCID:: 0000-0002-8717-0832

+ Li, Z More by this author

Institution:: University of Oxford
Role:: Author
ORCID:: 0000-0001-9431-258X

More authors...

+ National Institute for Health Research More from this funder

Funder identifier:: 10.13039/501100000272
Grant:: RP-2017-08-ST2-006

+ Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung More from this funder

Funder identifier:: 10.13039/501100001711
Grant:: 179158

Publisher:: BioMed Central
Journal:: BMC Psychiatry More from this journal
Volume:: 22
Issue:: 1
Pages:: 337-337
Article number:: 337
Publication date:: 2022-05-16
DOI:: 10.1186/s12888-022-03986-0
EISSN:: 1471-244X
ISSN:: 1471-244X

Language:: English
Keywords:: Econometrics

Outcome (game theory)

Medicine

Receiver operating characteristic

Statistics

Computer science

Perceptron

Binary number

Artificial neural network

Meta-analysis

Artificial intelligence

Machine learning

Regression

Mathematics

Bootstrapping (finance)

Multilayer perceptron
Pubs id:: 1260869
Local pid:: pubs:1260869
Source identifiers:: W4280531812
Deposit date:: 2026-04-24
ARK identifier:: ark:/29072/ora_3a75297fb5f24d9896f2bfd2f4a29451

Terms of use

Copyright date:: 2022

Licence:: CC Attribution (CC BY)

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