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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A hybrid metaheuristic-deep learning technique for the pan-classification of cancer based on DNA methylation
|
|---|---|
| Published in |
BMC Bioinformatics, July 2022
|
| DOI | 10.1186/s12859-022-04815-7 |
| Pubmed ID | |
| Authors |
Noureldin S. Eissa, Uswah Khairuddin, Rubiyah Yusof |
X Demographics
The data shown below were collected from the profiles of 14 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 | 3 | 21% |
| Israel | 1 | 7% |
| India | 1 | 7% |
| Sweden | 1 | 7% |
| United Kingdom | 1 | 7% |
| Unknown | 7 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 50% |
| Scientists | 6 | 43% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 4 | 15% |
| Lecturer | 2 | 8% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Student > Ph. D. Student | 1 | 4% |
| Student > Master | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 15 | 58% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 4 | 15% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Computer Science | 2 | 8% |
| Engineering | 2 | 8% |
| Medicine and Dentistry | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 14 | 54% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 16 June 2023.
All research outputs
#6,729,937
of 24,810,360 outputs
Outputs from BMC Bioinformatics
#2,383
of 7,591 outputs
Outputs of similar age
#121,023
of 426,917 outputs
Outputs of similar age from BMC Bioinformatics
#31
of 158 outputs
Altmetric has tracked 24,810,360 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,591 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 68% 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 426,917 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 71% of its contemporaries.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.