| Title |
GraphSynergy: a network-inspired deep learning model for anticancer drug combination prediction
|
|---|---|
| Published in |
Journal of the American Medical Informatics Association, September 2021
|
| DOI | 10.1093/jamia/ocab162 |
| Pubmed ID | |
| Authors |
Jiannan Yang, Zhongzhi Xu, William Ka Kei Wu, Qian Chu, Qingpeng Zhang |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 11% |
| Taiwan | 1 | 11% |
| South Africa | 1 | 11% |
| Unknown | 6 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 67% |
| Scientists | 2 | 22% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 17% |
| Student > Ph. D. Student | 6 | 14% |
| Student > Bachelor | 3 | 7% |
| Student > Master | 2 | 5% |
| Other | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 23 | 55% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 12% |
| Biochemistry, Genetics and Molecular Biology | 4 | 10% |
| Agricultural and Biological Sciences | 4 | 10% |
| Medicine and Dentistry | 2 | 5% |
| Physics and Astronomy | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 25 | 60% |
Attention Score in Context
This research output has an Altmetric Attention Score of 55. 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 12 June 2023.
All research outputs
#770,253
of 25,392,582 outputs
Outputs from Journal of the American Medical Informatics Association
#157
of 3,303 outputs
Outputs of similar age
#18,434
of 433,683 outputs
Outputs of similar age from Journal of the American Medical Informatics Association
#5
of 81 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,303 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.8. This one has done particularly well, scoring higher than 95% 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 433,683 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% 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 done particularly well, scoring higher than 93% of its contemporaries.