LoAdaBoost: Loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data

Intensive care data are valuable for improvement of health care, policy making and many other purposes. Vast amount of such data are stored in different locations, on many different devices and in different data silos. Sharing data among different sources is a big challenge due to regulatory, operat...

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Detalles Bibliográficos
Autores principales: Huang, Li, Yin, Yifeng, Fu, Zeng, Zhang, Shifa, Deng, Hao, Liu, Dianbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164603/
https://www.ncbi.nlm.nih.gov/pubmed/32302316
http://dx.doi.org/10.1371/journal.pone.0230706

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164603/
https://www.ncbi.nlm.nih.gov/pubmed/32302316
http://dx.doi.org/10.1371/journal.pone.0230706

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