The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19: A Theoretical Framework
|
|---|---|
| Published in |
Frontiers in Medicine, March 2021
|
| DOI | 10.3389/fmed.2021.585578 |
| Pubmed ID | |
| Authors |
Abdelkader Nasreddine Belkacem, Sofia Ouhbi, Abderrahmane Lakas, Elhadj Benkhelifa, Chao Chen |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 148 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 17 | 11% |
| Student > Ph. D. Student | 15 | 10% |
| Researcher | 14 | 9% |
| Lecturer | 10 | 7% |
| Student > Bachelor | 8 | 5% |
| Other | 19 | 13% |
| Unknown | 65 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 25 | 17% |
| Engineering | 17 | 11% |
| Medicine and Dentistry | 8 | 5% |
| Biochemistry, Genetics and Molecular Biology | 5 | 3% |
| Nursing and Health Professions | 4 | 3% |
| Other | 17 | 11% |
| Unknown | 72 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 24 March 2023.
All research outputs
#13,908,131
of 23,578,918 outputs
Outputs from Frontiers in Medicine
#2,303
of 6,092 outputs
Outputs of similar age
#208,455
of 432,833 outputs
Outputs of similar age from Frontiers in Medicine
#150
of 355 outputs
Altmetric has tracked 23,578,918 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,092 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.6. This one has gotten more attention than average, scoring higher than 59% 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 432,833 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 355 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 56% of its contemporaries.