| Title |
Federated learning for predicting clinical outcomes in patients with COVID-19
|
|---|---|
| Published in |
Nature Medicine, September 2021
|
| DOI | 10.1038/s41591-021-01506-3 |
| Pubmed ID | |
| Authors |
Ittai Dayan, Holger R. Roth, Aoxiao Zhong, Ahmed Harouni, Amilcare Gentili, Anas Z. Abidin, Andrew Liu, Anthony Beardsworth Costa, Bradford J. Wood, Chien-Sung Tsai, Chih-Hung Wang, Chun-Nan Hsu, C. K. Lee, Peiying Ruan, Daguang Xu, Dufan Wu, Eddie Huang, Felipe Campos Kitamura, Griffin Lacey, Gustavo César de Antônio Corradi, Gustavo Nino, Hao-Hsin Shin, Hirofumi Obinata, Hui Ren, Jason C. Crane, Jesse Tetreault, Jiahui Guan, John W. Garrett, Joshua D. Kaggie, Jung Gil Park, Keith Dreyer, Krishna Juluru, Kristopher Kersten, Marcio Aloisio Bezerra Cavalcanti Rockenbach, Marius George Linguraru, Masoom A. Haider, Meena AbdelMaseeh, Nicola Rieke, Pablo F. Damasceno, Pedro Mario Cruz e Silva, Pochuan Wang, Sheng Xu, Shuichi Kawano, Sira Sriswasdi, Soo Young Park, Thomas M. Grist, Varun Buch, Watsamon Jantarabenjakul, Weichung Wang, Won Young Tak, Xiang Li, Xihong Lin, Young Joon Kwon, Abood Quraini, Andrew Feng, Andrew N. Priest, Baris Turkbey, Benjamin Glicksberg, Bernardo Bizzo, Byung Seok Kim, Carlos Tor-Díez, Chia-Cheng Lee, Chia-Jung Hsu, Chin Lin, Chiu-Ling Lai, Christopher P. Hess, Colin Compas, Deepeksha Bhatia, Eric K. Oermann, Evan Leibovitz, Hisashi Sasaki, Hitoshi Mori, Isaac Yang, Jae Ho Sohn, Krishna Nand Keshava Murthy, Li-Chen Fu, Matheus Ribeiro Furtado de Mendonça, Mike Fralick, Min Kyu Kang, Mohammad Adil, Natalie Gangai, Peerapon Vateekul, Pierre Elnajjar, Sarah Hickman, Sharmila Majumdar, Shelley L. McLeod, Sheridan Reed, Stefan Gräf, Stephanie Harmon, Tatsuya Kodama, Thanyawee Puthanakit, Tony Mazzulli, Vitor Lima de Lavor, Yothin Rakvongthai, Yu Rim Lee, Yuhong Wen, Fiona J. Gilbert, Mona G. Flores, Quanzheng Li |
X Demographics
The data shown below were collected from the profiles of 179 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 59 | 33% |
| United Kingdom | 9 | 5% |
| France | 7 | 4% |
| Spain | 5 | 3% |
| India | 4 | 2% |
| Germany | 3 | 2% |
| Mexico | 3 | 2% |
| Belgium | 2 | 1% |
| Saudi Arabia | 2 | 1% |
| Other | 18 | 10% |
| Unknown | 67 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 122 | 68% |
| Scientists | 36 | 20% |
| Practitioners (doctors, other healthcare professionals) | 18 | 10% |
| Science communicators (journalists, bloggers, editors) | 3 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 387 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 387 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 46 | 12% |
| Student > Ph. D. Student | 45 | 12% |
| Student > Master | 30 | 8% |
| Student > Bachelor | 21 | 5% |
| Unspecified | 12 | 3% |
| Other | 58 | 15% |
| Unknown | 175 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 64 | 17% |
| Medicine and Dentistry | 37 | 10% |
| Engineering | 23 | 6% |
| Unspecified | 12 | 3% |
| Mathematics | 7 | 2% |
| Other | 52 | 13% |
| Unknown | 192 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 464. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 February 2024.
All research outputs
#60,417
of 25,930,027 outputs
Outputs from Nature Medicine
#367
of 9,490 outputs
Outputs of similar age
#1,820
of 437,291 outputs
Outputs of similar age from Nature Medicine
#16
of 106 outputs
Altmetric has tracked 25,930,027 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,490 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 106.7. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 437,291 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 106 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.