| Title |
Comparison of deep learning with regression analysis in creating predictive models for SARS-CoV-2 outcomes
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2020
|
| DOI | 10.1186/s12911-020-01316-6 |
| Pubmed ID | |
| Authors |
Ahmed Abdulaal, Aatish Patel, Esmita Charani, Sarah Denny, Saleh A. Alqahtani, Gary W. Davies, Nabeela Mughal, Luke S. P. Moore |
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 % |
|---|---|---|
| South Africa | 1 | 20% |
| Switzerland | 1 | 20% |
| France | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 1 | 20% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 132 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 14% |
| Researcher | 14 | 11% |
| Student > Ph. D. Student | 11 | 8% |
| Student > Bachelor | 11 | 8% |
| Other | 8 | 6% |
| Other | 21 | 16% |
| Unknown | 48 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 17% |
| Computer Science | 13 | 10% |
| Nursing and Health Professions | 8 | 6% |
| Engineering | 8 | 6% |
| Biochemistry, Genetics and Molecular Biology | 6 | 5% |
| Other | 21 | 16% |
| Unknown | 53 | 40% |
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 08 February 2021.
All research outputs
#13,211,869
of 23,278,709 outputs
Outputs from BMC Medical Informatics and Decision Making
#897
of 2,023 outputs
Outputs of similar age
#227,046
of 507,382 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#16
of 53 outputs
Altmetric has tracked 23,278,709 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,023 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 53% 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 507,382 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 54% of its contemporaries.
We're also able to compare this research output to 53 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 66% of its contemporaries.