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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Robust Machine Learning for Colorectal Cancer Risk Prediction and Stratification
|
|---|---|
| Published in |
Frontiers in Big Data, March 2020
|
| DOI | 10.3389/fdata.2020.00006 |
| Pubmed ID | |
| Authors |
Bradley J. Nartowt, Gregory R. Hart, Wazir Muhammad, Ying Liang, Gigi F. Stark, Jun Deng |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 14% |
| United Arab Emirates | 1 | 14% |
| United States | 1 | 14% |
| Switzerland | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 1 | 14% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 60 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 17% |
| Student > Master | 7 | 12% |
| Student > Bachelor | 6 | 10% |
| Researcher | 4 | 7% |
| Lecturer | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 25 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 13% |
| Medicine and Dentistry | 7 | 12% |
| Biochemistry, Genetics and Molecular Biology | 3 | 5% |
| Engineering | 2 | 3% |
| Mathematics | 2 | 3% |
| Other | 8 | 13% |
| Unknown | 30 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 18 August 2022.
All research outputs
#6,692,511
of 25,992,468 outputs
Outputs from Frontiers in Big Data
#1
of 1 outputs
Outputs of similar age
#120,996
of 390,655 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 has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. 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 390,655 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 68% of its contemporaries.
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