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X Demographics
Mendeley readers
Attention Score in Context
| Title |
COVID-19 Prediction With Machine Learning Technique From Extracted Features of Photoplethysmogram Morphology
|
|---|---|
| Published in |
Frontiers in Public Health, July 2022
|
| DOI | 10.3389/fpubh.2022.920849 |
| Pubmed ID | |
| Authors |
Nazrul Anuar Nayan, Choon Jie Yi, Mohd Zubir Suboh, Nur-Fadhilah Mazlan, Petrick Periyasamy, Muhammad Yusuf Zawir Abdul Rahim, Shamsul Azhar Shah |
X Demographics
The data shown below were collected from the profiles of 3 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 Kingdom | 2 | 67% |
| Switzerland | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 15% |
| Student > Master | 2 | 10% |
| Unspecified | 1 | 5% |
| Student > Ph. D. Student | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 10 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 20% |
| Chemistry | 2 | 10% |
| Computer Science | 1 | 5% |
| Unspecified | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 10 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 20 July 2022.
All research outputs
#17,816,222
of 22,888,307 outputs
Outputs from Frontiers in Public Health
#5,005
of 10,025 outputs
Outputs of similar age
#284,074
of 434,273 outputs
Outputs of similar age from Frontiers in Public Health
#510
of 1,217 outputs
Altmetric has tracked 22,888,307 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,025 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 434,273 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,217 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.