Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Mackenzie Edmondson"'
Autor:
Jiayi Tong, Chongliang Luo, Md Nazmul Islam, Natalie E. Sheils, John Buresh, Mackenzie Edmondson, Peter A. Merkel, Ebbing Lautenbach, Rui Duan, Yong Chen
Publikováno v:
npj Digital Medicine, Vol 5, Iss 1, Pp 1-8 (2022)
Abstract Integrating real-world data (RWD) from several clinical sites offers great opportunities to improve estimation with a more general population compared to analyses based on a single clinical site. However, sharing patient-level data across si
Externí odkaz:
https://doaj.org/article/8fe9ce2efb5b4f619682f7decc10a378
Autor:
Chongliang Luo, Md. Nazmul Islam, Natalie E. Sheils, John Buresh, Jenna Reps, Martijn J. Schuemie, Patrick B. Ryan, Mackenzie Edmondson, Rui Duan, Jiayi Tong, Arielle Marks-Anglin, Jiang Bian, Zhaoyi Chen, Talita Duarte-Salles, Sergio Fernández-Bertolín, Thomas Falconer, Chungsoo Kim, Rae Woong Park, Stephen R. Pfohl, Nigam H. Shah, Andrew E. Williams, Hua Xu, Yujia Zhou, Ebbing Lautenbach, Jalpa A. Doshi, Rachel M. Werner, David A. Asch, Yong Chen
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-10 (2022)
A lossless, one-shot and privacy-preserving distributed algorithm was revealed for fitting linear mixed models on multi-site data. The algorithm was applied to a study of 120,609 COVID-19 patients using only minimal aggregated data from each of 14 si
Externí odkaz:
https://doaj.org/article/c7bac154e8d74bfa915f9fc9df810e06
Autor:
Chongliang Luo, Md. Nazmul Islam, Natalie E. Sheils, John Buresh, Jenna Reps, Martijn J. Schuemie, Patrick B. Ryan, Mackenzie Edmondson, Rui Duan, Jiayi Tong, Arielle Marks-Anglin, Jiang Bian, Zhaoyi Chen, Talita Duarte-Salles, Sergio Fernández-Bertolín, Thomas Falconer, Chungsoo Kim, Rae Woong Park, Stephen R. Pfohl, Nigam H. Shah, Andrew E. Williams, Hua Xu, Yujia Zhou, Ebbing Lautenbach, Jalpa A. Doshi, Rachel M. Werner, David A. Asch, Yong Chen
Publikováno v:
Nature communications. 13(1)
Linear mixed models are commonly used in healthcare-based association analyses for analyzing multi-site data with heterogeneous site-specific random effects. Due to regulations for protecting patients’ privacy, sensitive individual patient data (IP