| Title |
Health Data-Driven Machine Learning Algorithms Applied to Risk Indicators Assessment for Chronic Kidney Disease
|
|---|---|
| Published in |
Risk Management and Healthcare Policy, October 2021
|
| DOI | 10.2147/rmhp.s319405 |
| Pubmed ID | |
| Authors |
Yen-Ling Chiu, Mao-Jhen Jhou, Tian-Shyug Lee, Chi-Jie Lu, Ming-Shu Chen |
X Demographics
The data shown below were collected from the profiles of 6 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 | 50% |
| Ukraine | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Lecturer | 7 | 20% |
| Student > Master | 2 | 6% |
| Student > Ph. D. Student | 2 | 6% |
| Student > Doctoral Student | 1 | 3% |
| Student > Bachelor | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 18 | 51% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 4 | 11% |
| Computer Science | 3 | 9% |
| Medicine and Dentistry | 3 | 9% |
| Nursing and Health Professions | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 19 | 54% |
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 01 November 2021.
All research outputs
#15,484,645
of 24,998,746 outputs
Outputs from Risk Management and Healthcare Policy
#318
of 715 outputs
Outputs of similar age
#214,059
of 427,484 outputs
Outputs of similar age from Risk Management and Healthcare Policy
#29
of 62 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 715 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one has gotten more attention than average, scoring higher than 54% 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 427,484 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 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 53% of its contemporaries.