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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A deep learning model for predicting COVID-19 ARDS in critically ill patients
|
|---|---|
| Published in |
Frontiers in Medicine, July 2023
|
| DOI | 10.3389/fmed.2023.1221711 |
| Pubmed ID | |
| Authors |
Yang Zhou, Jinhua Feng, Shuya Mei, Ri Tang, Shunpeng Xing, Shaojie Qin, Zhiyun Zhang, Qiaoyi Xu, Yuan Gao, Zhengyu He |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor | 1 | 14% |
| Student > Doctoral Student | 1 | 14% |
| Unknown | 5 | 71% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 29% |
| Unknown | 5 | 71% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 31 July 2023.
All research outputs
#2,283,412
of 24,174,783 outputs
Outputs from Frontiers in Medicine
#598
of 6,480 outputs
Outputs of similar age
#18,391
of 179,484 outputs
Outputs of similar age from Frontiers in Medicine
#5
of 137 outputs
Altmetric has tracked 24,174,783 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,480 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one has done particularly well, scoring higher than 90% 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 179,484 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.