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 |
Interpretability of Machine Learning Solutions in Public Healthcare: The CRISP-ML Approach
|
|---|---|
| Published in |
Frontiers in Big Data, May 2021
|
| DOI | 10.3389/fdata.2021.660206 |
| Pubmed ID | |
| Authors |
Inna Kolyshkina, Simeon Simoff |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 50% |
| Switzerland | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 125 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 10% |
| Student > Master | 13 | 10% |
| Researcher | 7 | 6% |
| Student > Doctoral Student | 6 | 5% |
| Lecturer | 6 | 5% |
| Other | 9 | 7% |
| Unknown | 71 | 57% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 11% |
| Business, Management and Accounting | 9 | 7% |
| Engineering | 9 | 7% |
| Medicine and Dentistry | 3 | 2% |
| Biochemistry, Genetics and Molecular Biology | 3 | 2% |
| Other | 12 | 10% |
| Unknown | 75 | 60% |
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 September 2021.
All research outputs
#17,012,522
of 25,992,468 outputs
Outputs from Frontiers in Big Data
#1
of 1 outputs
Outputs of similar age
#266,076
of 463,789 outputs
Outputs of similar age from Frontiers in Big Data
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 1.4. This one scored the same or higher as 0 of them.
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 463,789 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them