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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, February 2021
|
| DOI | 10.1186/s12911-020-01359-9 |
| Pubmed ID | |
| Authors |
Chenxi Sun, Shenda Hong, Moxian Song, Hongyan Li, Zhenjie Wang |
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 % |
|---|---|---|
| Hong Kong | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 130 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 12% |
| Researcher | 15 | 12% |
| Student > Ph. D. Student | 12 | 9% |
| Lecturer | 7 | 5% |
| Student > Doctoral Student | 7 | 5% |
| Other | 20 | 15% |
| Unknown | 53 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 18% |
| Computer Science | 18 | 14% |
| Nursing and Health Professions | 8 | 6% |
| Engineering | 7 | 5% |
| Social Sciences | 3 | 2% |
| Other | 14 | 11% |
| Unknown | 57 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 10 August 2023.
All research outputs
#2,333,967
of 24,244,537 outputs
Outputs from BMC Medical Informatics and Decision Making
#143
of 2,066 outputs
Outputs of similar age
#66,165
of 517,206 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 56 outputs
Altmetric has tracked 24,244,537 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 2,066 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 93% 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 517,206 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 87% of its contemporaries.
We're also able to compare this research output to 56 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 92% of its contemporaries.