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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning algorithm for early detection of end-stage renal disease
|
|---|---|
| Published in |
BMC Nephrology, November 2020
|
| DOI | 10.1186/s12882-020-02093-0 |
| Pubmed ID | |
| Authors |
Zvi Segal, Dan Kalifa, Kira Radinsky, Bar Ehrenberg, Guy Elad, Gal Maor, Maor Lewis, Muhammad Tibi, Liat Korn, Gideon Koren |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Israel | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 92 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 14% |
| Student > Bachelor | 8 | 9% |
| Researcher | 6 | 7% |
| Student > Ph. D. Student | 6 | 7% |
| Student > Doctoral Student | 4 | 4% |
| Other | 9 | 10% |
| Unknown | 46 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 16 | 17% |
| Medicine and Dentistry | 9 | 10% |
| Engineering | 6 | 7% |
| Nursing and Health Professions | 6 | 7% |
| Business, Management and Accounting | 3 | 3% |
| Other | 7 | 8% |
| Unknown | 45 | 49% |
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 07 December 2020.
All research outputs
#13,005,380
of 23,267,128 outputs
Outputs from BMC Nephrology
#955
of 2,512 outputs
Outputs of similar age
#220,551
of 509,387 outputs
Outputs of similar age from BMC Nephrology
#34
of 81 outputs
Altmetric has tracked 23,267,128 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,512 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 61% 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 509,387 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 56% of its contemporaries.
We're also able to compare this research output to 81 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 58% of its contemporaries.