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X Demographics
Mendeley readers
Attention Score in Context
Title |
Can Clinical Symptoms and Laboratory Results Predict CT Abnormality? Initial Findings Using Novel Machine Learning Techniques in Children With COVID-19 Infections
|
---|---|
Published in |
Frontiers in Medicine, June 2021
|
DOI | 10.3389/fmed.2021.699984 |
Pubmed ID | |
Authors |
Huijing Ma, Qinghao Ye, Weiping Ding, Yinghui Jiang, Minhao Wang, Zhangming Niu, Xi Zhou, Yuan Gao, Chengjia Wang, Wade Menpes-Smith, Evandro Fei Fang, Jianbo Shao, Jun Xia, Guang Yang |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 20% |
United States | 1 | 20% |
Unknown | 3 | 60% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 55 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 8 | 15% |
Other | 3 | 5% |
Student > Bachelor | 3 | 5% |
Researcher | 3 | 5% |
Student > Ph. D. Student | 3 | 5% |
Other | 6 | 11% |
Unknown | 29 | 53% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 9 | 16% |
Computer Science | 3 | 5% |
Business, Management and Accounting | 2 | 4% |
Chemical Engineering | 1 | 2% |
Nursing and Health Professions | 1 | 2% |
Other | 6 | 11% |
Unknown | 33 | 60% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 July 2021.
All research outputs
#13,748,377
of 23,308,124 outputs
Outputs from Frontiers in Medicine
#2,249
of 5,969 outputs
Outputs of similar age
#203,059
of 446,909 outputs
Outputs of similar age from Frontiers in Medicine
#154
of 414 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,969 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has gotten more attention than average, scoring higher than 60% 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 446,909 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 414 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.