Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals

Tsung-Ting Kuo; Rodney A. Gabriel; Jejo Koola; Robert T. Schooley; Lucila Ohno-Machado

doi:10.1038/s41467-025-56510-9

Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals

T Tsung-Ting Kuo R Rodney A. Gabriel (Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego) J Jejo Koola R Robert T. Schooley L Lucila Ohno-Machado

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Article Details

Journal Nature Communications

Volume / Issue Vol. 16, Issue 1

Published February 05, 2025

DOI 10.1038/s41467-025-56510-9

ISSN 2041-1723

Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (5)

T

Tsung-Ting Kuo

R

Rodney A. Gabriel

Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego

J

Jejo Koola

R

Robert T. Schooley

L

Lucila Ohno-Machado

Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals

Article Details

Journal Info

Authors (5)

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