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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Application of Machine Learning in Diagnosis of COVID-19 Through X-Ray and CT Images: A Scoping Review
|
|---|---|
| Published in |
Frontiers in Cardiovascular Medicine, March 2021
|
| DOI | 10.3389/fcvm.2021.638011 |
| Pubmed ID | |
| Authors |
Hossein Mohammad-Rahimi, Mohadeseh Nadimi, Azadeh Ghalyanchi-Langeroudi, Mohammad Taheri, Soudeh Ghafouri-Fard |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 20% |
| Switzerland | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 153 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 10% |
| Student > Ph. D. Student | 13 | 8% |
| Student > Bachelor | 13 | 8% |
| Researcher | 11 | 7% |
| Student > Doctoral Student | 9 | 6% |
| Other | 24 | 16% |
| Unknown | 67 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 28 | 18% |
| Engineering | 22 | 14% |
| Medicine and Dentistry | 9 | 6% |
| Agricultural and Biological Sciences | 5 | 3% |
| Biochemistry, Genetics and Molecular Biology | 5 | 3% |
| Other | 13 | 8% |
| Unknown | 71 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 01 May 2021.
All research outputs
#13,665,626
of 23,295,606 outputs
Outputs from Frontiers in Cardiovascular Medicine
#1,592
of 7,192 outputs
Outputs of similar age
#204,443
of 429,395 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#85
of 317 outputs
Altmetric has tracked 23,295,606 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,192 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 77% 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 429,395 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 51% of its contemporaries.
We're also able to compare this research output to 317 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 72% of its contemporaries.