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Timeline
X Demographics
Mendeley readers
Attention Score in Context
Title |
Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study
|
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Published in |
Frontiers in Public Health, February 2023
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DOI | 10.3389/fpubh.2023.1063466 |
Pubmed ID | |
Authors |
Lily Wei Yun Yang, Wei Yan Ng, Xiaofeng Lei, Shaun Chern Yuan Tan, Zhaoran Wang, Ming Yan, Mohan Kashyap Pargi, Xiaoman Zhang, Jane Sujuan Lim, Dinesh Visva Gunasekeran, Franklin Chee Ping Tan, Chen Ee Lee, Khung Keong Yeo, Hiang Khoon Tan, Henry Sun Sien Ho, Benedict Wee Bor Tan, Tien Yin Wong, Kenneth Yung Chiang Kwek, Rick Siow Mong Goh, Yong Liu, Daniel Shu Wei Ting |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 50% |
Switzerland | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 63 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 4 | 6% |
Student > Bachelor | 4 | 6% |
Unspecified | 3 | 5% |
Lecturer | 2 | 3% |
Student > Postgraduate | 2 | 3% |
Other | 7 | 11% |
Unknown | 41 | 65% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 5 | 8% |
Business, Management and Accounting | 5 | 8% |
Computer Science | 3 | 5% |
Unspecified | 3 | 5% |
Mathematics | 1 | 2% |
Other | 6 | 10% |
Unknown | 40 | 63% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 02 March 2023.
All research outputs
#21,566,851
of 26,473,472 outputs
Outputs from Frontiers in Public Health
#8,498
of 14,996 outputs
Outputs of similar age
#379,673
of 506,859 outputs
Outputs of similar age from Frontiers in Public Health
#657
of 1,348 outputs
Altmetric has tracked 26,473,472 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,996 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 506,859 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,348 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.