| Title |
Scalable deep text comprehension for Cancer surveillance on high-performance computing
|
|---|---|
| Published in |
BMC Bioinformatics, December 2018
|
| DOI | 10.1186/s12859-018-2511-9 |
| Pubmed ID | |
| Authors |
John X. Qiu, Hong-Jun Yoon, Kshitij Srivastava, Thomas P. Watson, J. Blair Christian, Arvind Ramanathan, Xiao C. Wu, Paul A. Fearn, Georgia D. Tourassi |
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 % |
|---|---|---|
| United Kingdom | 2 | 50% |
| France | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 20% |
| Student > Ph. D. Student | 7 | 17% |
| Student > Bachelor | 4 | 10% |
| Student > Doctoral Student | 3 | 7% |
| Researcher | 3 | 7% |
| Other | 6 | 15% |
| Unknown | 10 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 20% |
| Computer Science | 8 | 20% |
| Agricultural and Biological Sciences | 4 | 10% |
| Nursing and Health Professions | 1 | 2% |
| Business, Management and Accounting | 1 | 2% |
| Other | 7 | 17% |
| Unknown | 12 | 29% |
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 24 December 2018.
All research outputs
#15,268,318
of 24,226,848 outputs
Outputs from BMC Bioinformatics
#4,863
of 7,512 outputs
Outputs of similar age
#243,729
of 444,213 outputs
Outputs of similar age from BMC Bioinformatics
#129
of 206 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,512 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 444,213 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 206 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.