Browsing Faculty of Arts and Sciences by Author "Garrett, John W."

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    • Federated Learning for Predicting Clinical Outcomes in COVID-19 Patients 

      Dayan, Ittai; Roth, Holger; Zhong, Aoxiao; Harouni, Ahmed; Gentili, Amilcare; Abidin, Anas; Liu, Andrew; Costa, Anthony Beardsworth; Wood, Bradford J.; Tsai, Chien-Sung; Wang, Chih-Hung; Hsu, Chun-Nan; Lee, CK; Ruan, Peiying; Xu, Daguang; Wu, Dufan; Huang, Eddie; Kitamura, Felipe Campos; Lacey, Griffin; Corradi, Gustavo César de Antônio; Nino Furnieles, Gustavo; Shin, Hao-Hsin; Obinata, Hirofumi; Ren, Hui; Crane, Jason C.; Tetreault, Jesse; Guan, Jiahui; Garrett, John W.; Kaggie, Josh D; Park, Jung Gil; Dreyer, Keith; Juluru, Krishna; Kersten, Kristopher; Rockenbach, Marcio Aloisio Bezerra Cavalcanti; Linguraru, Marius George; Haider, Masoom A.; AbdelMaseeh, Meena; Rieke, Nicola; Damasceno, Pablo F.; Silva, Pedro Mario Cruz e; Wang, Pochuan; Xu, Sheng; Kawano, Shuichi; Sriswasdi, Sira; Park, Soo-Young; Grist, Thomas M; Buch, Varun; Jantarabenjakul, Watsamon; Wang, Weichung; Tak, Won Young; Li, Xiang; Lin, Xihong; Kwon, Young Joon; Quraini, Abood; Feng, Andrew; Priest, Andrew N; Turkbey, Baris; Glicksberg, Benjamin; Canedo Bizzo, Bernardo; Kim, Byung Seok; Tor-Díez, Carlos; Lee, Chia-Cheng; Hsu, Chia-Jung; Lin, Chin; Lai, Chiu-Ling; Hess, Christopher P.; Compas, Colin; Bhatia, Deepeksha; Oermann, Eric K; Leibovitz, Evan; Sasaki, Hisashi; Mori, Hitoshi; Yang, Isaac; Sohn, Jae Ho; Murthy, Krishna Nand Keshava; Fu, Li-Chen; Mendonça, Matheus Ribeiro Furtado de; Fralick, Mike; Kang, Min Kyu; Adil, Mohammad; Gangai, Natalie; Vateekul, Peerapon; Elnajjar, Pierre; Hickman, Sarah; Majumdar, Sharmila; McLeod, Shelley L.; Reed, Sheridan; Graf, Stefan; Harmon, Stephanie; Kodama, Tatsuya; Puthanakit, Thanyawee; Mazzulli, Tony; Lavor, Vitor de Lima; Rakvongthai, Yothin; Lee, Yu Rim; Wen, Yuhong; Gilbert, Fiona J; Flores, Mona G.; Li, Quanzheng (2021-09-15)
      Federated learning (FL) is a method for training artificial intelligence (AI) models with data from multiple sources while maintaining the anonymity of the data, thus removing many barriers to data sharing. Here we use ...