| Title |
Pancreatic Ductal Adenocarcinoma: Machine Learning–Based Quantitative Computed Tomography Texture Analysis For Prediction Of Histopathological Grade
|
|---|---|
| Published in |
Cancer Management and Research, October 2019
|
| DOI | 10.2147/cmar.s218414 |
| Pubmed ID | |
| Authors |
Wenli Qiu, Na Duan, Xiao Chen, Shuai Ren, Yifen Zhang, Zhongqiu Wang, Rong Chen |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| Germany | 1 | 33% |
| United States | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 16% |
| Student > Bachelor | 5 | 13% |
| Student > Postgraduate | 4 | 11% |
| Student > Master | 4 | 11% |
| Other | 3 | 8% |
| Other | 9 | 24% |
| Unknown | 7 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 34% |
| Engineering | 5 | 13% |
| Computer Science | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Psychology | 1 | 3% |
| Other | 5 | 13% |
| Unknown | 10 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 07 December 2019.
All research outputs
#17,141,620
of 25,182,110 outputs
Outputs from Cancer Management and Research
#791
of 2,066 outputs
Outputs of similar age
#224,553
of 356,932 outputs
Outputs of similar age from Cancer Management and Research
#26
of 79 outputs
Altmetric has tracked 25,182,110 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,066 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 50% 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 356,932 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 79 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 58% of its contemporaries.