Sequential autoencoders for feature engineering and pretraining in major depressive disorder risk prediction

OBJECTIVES: We evaluated autoencoders as a feature engineering and pretraining technique to improve major depressive disorder (MDD) prognostic risk prediction. Autoencoders can represent temporal feature relationships not identified by aggregate features. The predictive performance of autoencoders o...

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Detalles Bibliográficos
Autores principales: Jones, Barrett W, Taylor, Warren D, Walsh, Colin G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10561992/
https://www.ncbi.nlm.nih.gov/pubmed/37818308
http://dx.doi.org/10.1093/jamiaopen/ooad086

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10561992/
https://www.ncbi.nlm.nih.gov/pubmed/37818308
http://dx.doi.org/10.1093/jamiaopen/ooad086

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