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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models
|
|---|---|
| Published in |
Breast Cancer Research, June 2019
|
| DOI | 10.1186/s13058-019-1158-4 |
| Pubmed ID | |
| Authors |
Chang Ming, Valeria Viassolo, Nicole Probst-Hensch, Pierre O. Chappuis, Ivo D. Dinov, Maria C. Katapodi |
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 % |
|---|---|---|
| Egypt | 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 229 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 229 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 42 | 18% |
| Researcher | 23 | 10% |
| Student > Bachelor | 22 | 10% |
| Student > Master | 18 | 8% |
| Lecturer | 12 | 5% |
| Other | 38 | 17% |
| Unknown | 74 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 46 | 20% |
| Medicine and Dentistry | 30 | 13% |
| Engineering | 17 | 7% |
| Nursing and Health Professions | 14 | 6% |
| Biochemistry, Genetics and Molecular Biology | 7 | 3% |
| Other | 33 | 14% |
| Unknown | 82 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 10 September 2020.
All research outputs
#3,183,807
of 25,651,057 outputs
Outputs from Breast Cancer Research
#333
of 2,062 outputs
Outputs of similar age
#63,624
of 368,068 outputs
Outputs of similar age from Breast Cancer Research
#8
of 26 outputs
Altmetric has tracked 25,651,057 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,062 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.3. This one has done well, scoring higher than 83% 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 368,068 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 82% of its contemporaries.
We're also able to compare this research output to 26 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 69% of its contemporaries.