The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries
|
|---|---|
| Published in |
Frontiers in Cardiovascular Medicine, March 2022
|
| DOI | 10.3389/fcvm.2022.839379 |
| Pubmed ID | |
| Authors |
Mohammed Shariful Islam, Ashis Talukder, Abdul Awal, Muhammad Umer Siddiqui, Martuza Ahamad, Benojir Ahammed, Lal B. Rawal, Roohallah Alizadehsani, Jemal Abawajy, Liliana Laranjo, Clara K. Chow, Ralph Maddison |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 2 | 17% |
| United States | 2 | 17% |
| Iceland | 1 | 8% |
| Switzerland | 1 | 8% |
| Bangladesh | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 75% |
| Scientists | 3 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 85 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 9% |
| Student > Bachelor | 7 | 8% |
| Student > Doctoral Student | 5 | 6% |
| Lecturer | 5 | 6% |
| Researcher | 5 | 6% |
| Other | 13 | 15% |
| Unknown | 42 | 49% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 15% |
| Medicine and Dentistry | 6 | 7% |
| Unspecified | 4 | 5% |
| Nursing and Health Professions | 3 | 4% |
| Engineering | 3 | 4% |
| Other | 13 | 15% |
| Unknown | 43 | 51% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 13 February 2023.
All research outputs
#4,800,154
of 26,547,438 outputs
Outputs from Frontiers in Cardiovascular Medicine
#757
of 9,576 outputs
Outputs of similar age
#99,854
of 455,379 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#98
of 991 outputs
Altmetric has tracked 26,547,438 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,576 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 92% 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 455,379 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 991 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.