dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning

MOTIVATION: In multi-cohort machine learning studies, it is critical to differentiate between effects that are reproducible across cohorts and those that are cohort-specific. Multi-task learning (MTL) is a machine learning approach that facilitates this differentiation through the simultaneous learn...

Descripción completa

Detalles Bibliográficos
Autores principales: Cao, Han, Zhang, Youcheng, Baumbach, Jan, Burton, Paul R, Dwyer, Dominic, Koutsouleris, Nikolaos, Matschinske, Julian, Marcon, Yannick, Rajan, Sivanesan, Rieg, Thilo, Ryser-Welch, Patricia, Späth, Julian, Herrmann, Carl, Schwarz, Emanuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620828/
https://www.ncbi.nlm.nih.gov/pubmed/36073911
http://dx.doi.org/10.1093/bioinformatics/btac616

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620828/
https://www.ncbi.nlm.nih.gov/pubmed/36073911
http://dx.doi.org/10.1093/bioinformatics/btac616

Ejemplares similares