Federated Learning used for predicting outcomes in SARS-COV-2 patients

‘Federated Learning’ (FL) is a method to train Artificial Intelligence (AI) models with data from multiple sources while maintaining anonymity of the data thus removing many barriers to data sharing. During the SARS-COV-2 pandemic, 20 institutes collaborated on a healthcare FL study to predict futur...

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Detalles Bibliográficos
Autores principales: Flores, Mona, Dayan, Ittai, Roth, Holger, Zhong, Aoxiao, Harouni, Ahmed, Gentili, Amilcare, Abidin, Anas, Liu, Andrew, Costa, Anthony, Wood, Bradford, Tsai, Chien-Sung, Wang, Chih-Hung, Hsu, Chun-Nan, Lee, CK, Ruan, Colleen, Xu, Daguang, Wu, Dufan, Huang, Eddie, Kitamura, Felipe, Lacey, Griffin, César de Antônio Corradi, Gustavo, Shin, Hao-Hsin, Obinata, Hirofumi, Ren, Hui, Crane, Jason, Tetreault, Jesse, Guan, Jiahui, Garrett, John, Park, Jung Gil, Dreyer, Keith, Juluru, Krishna, Kersten, Kristopher, Bezerra Cavalcanti Rockenbach, Marcio Aloisio, Linguraru, Marius, Haider, Masoom, AbdelMaseeh, Meena, Rieke, Nicola, Damasceno, Pablo, Cruz e Silva, Pedro Mario, Wang, Pochuan, Xu, Sheng, Kawano, Shuichi, Sriswasdi, Sira, Park, Soo Young, Grist, Thomas, Buch, Varun, Jantarabenjakul, Watsamon, Wang, Weichung, Tak, Won Young, Li, Xiang, Lin, Xihong, Kwon, Fred, Gilbert, Fiona, Kaggie, Josh, Li, Quanzheng, Quraini, Abood, Feng, Andrew, Priest, Andrew, Turkbey, Baris, Glicksberg, Benjamin, Bizzo, Bernardo, Kim, Byung Seok, Tor-Diez, Carlos, Lee, Chia-Cheng, Hsu, Chia-Jung, Lin, Chin, Lai, Chiu-Ling, Hess, Christopher, Compas, Colin, Bhatia, Deepi, Oermann, Eric, Leibovitz, Evan, Sasaki, Hisashi, Mori, Hitoshi, Yang, Isaac, Sohn, Jae Ho, Keshava Murthy, Krishna Nand, Fu, Li-Chen, Furtado de Mendonça, Matheus Ribeiro, Fralick, Mike, Kang, Min Kyu, Adil, Mohammad, Gangai, Natalie, Vateekul, Peerapon, Elnajjar, Pierre, Hickman, Sarah, Majumdar, Sharmila, McLeod, Shelley, Reed, Sheridan, Graf, Stefan, Harmon, Stephanie, Kodama, Tatsuya, Puthanakit, Thanyawee, Mazzulli, Tony, de Lima Lavor, Vitor, Rakvongthai, Yothin, Lee, Yu Rim, Wen, Yuhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805458/
https://www.ncbi.nlm.nih.gov/pubmed/33442676
http://dx.doi.org/10.21203/rs.3.rs-126892/v1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805458/
https://www.ncbi.nlm.nih.gov/pubmed/33442676
http://dx.doi.org/10.21203/rs.3.rs-126892/v1

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