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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Classification of COVID-19 electrocardiograms by using hexaxial feature mapping and deep learning
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, May 2021
|
| DOI | 10.1186/s12911-021-01521-x |
| Pubmed ID | |
| Authors |
Mehmet Akif Ozdemir, Gizem Dilara Ozdemir, Onan Guren |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 20% |
| Australia | 1 | 10% |
| Kenya | 1 | 10% |
| United Kingdom | 1 | 10% |
| Unknown | 5 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Practitioners (doctors, other healthcare professionals) | 2 | 20% |
| Scientists | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 97 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 12% |
| Student > Ph. D. Student | 9 | 9% |
| Student > Bachelor | 9 | 9% |
| Researcher | 8 | 8% |
| Other | 4 | 4% |
| Other | 12 | 12% |
| Unknown | 43 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 16 | 16% |
| Computer Science | 8 | 8% |
| Medicine and Dentistry | 7 | 7% |
| Nursing and Health Professions | 4 | 4% |
| Biochemistry, Genetics and Molecular Biology | 3 | 3% |
| Other | 14 | 14% |
| Unknown | 45 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 05 October 2021.
All research outputs
#6,503,217
of 25,360,284 outputs
Outputs from BMC Medical Informatics and Decision Making
#562
of 2,139 outputs
Outputs of similar age
#129,754
of 441,560 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#18
of 59 outputs
Altmetric has tracked 25,360,284 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 2,139 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 73% 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 441,560 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 70% of its contemporaries.
We're also able to compare this research output to 59 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 71% of its contemporaries.