Development of a federated learning approach to predict acute kidney injury in adult hospitalized patients with COVID-19 in New York City

Federated learning is a technique for training predictive models without sharing patient-level data, thus maintaining data security while allowing inter-institutional collaboration. We used federated learning to predict acute kidney injury within three and seven days of admission, using demographics...

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Detalles Bibliográficos
Autores principales: Jaladanki, Suraj K, Vaid, Akhil, Sawant, Ashwin S, Xu, Jie, Shah, Kush, Dellepiane, Sergio, Paranjpe, Ishan, Chan, Lili, Kovatch, Patricia, Charney, Alexander W, Wang, Fei, Glicksberg, Benjamin S, Singh, Karandeep, Nadkarni, Girish N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328073/
https://www.ncbi.nlm.nih.gov/pubmed/34341802
http://dx.doi.org/10.1101/2021.07.25.21261105

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328073/
https://www.ncbi.nlm.nih.gov/pubmed/34341802
http://dx.doi.org/10.1101/2021.07.25.21261105

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