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Federated learning for predicting clinical outcomes in patients with COVID-19

Overview of attention for article published in Nature Medicine, September 2021
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

news
48 news outlets
blogs
3 blogs
twitter
180 X users
patent
1 patent
facebook
1 Facebook page
wikipedia
2 Wikipedia pages
reddit
1 Redditor

Readers on

mendeley
384 Mendeley
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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

X Demographics

The data shown below were collected from the profiles of 180 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 384 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 384 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 46 12%
Student > Ph. D. Student 44 11%
Student > Master 30 8%
Student > Bachelor 21 5%
Unspecified 19 5%
Other 58 15%
Unknown 166 43%
Readers by discipline Count As %
Computer Science 62 16%
Medicine and Dentistry 36 9%
Engineering 24 6%
Unspecified 20 5%
Agricultural and Biological Sciences 8 2%
Other 51 13%
Unknown 183 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 465. 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
#59,472
of 25,738,558 outputs
Outputs from Nature Medicine
#363
of 9,412 outputs
Outputs of similar age
#1,806
of 436,070 outputs
Outputs of similar age from Nature Medicine
#16
of 106 outputs
Altmetric has tracked 25,738,558 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 9,412 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 105.8. 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 436,070 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.