The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Development and Validation of a Deep Neural Network for Accurate Identification of Endoscopic Images From Patients With Ulcerative Colitis and Crohn's Disease
|
|---|---|
| Published in |
Frontiers in Medicine, March 2022
|
| DOI | 10.3389/fmed.2022.854677 |
| Pubmed ID | |
| Authors |
Guangcong Ruan, Jing Qi, Yi Cheng, Rongbei Liu, Bingqiang Zhang, Min Zhi, Junrong Chen, Fang Xiao, Xiaochun Shen, Ling Fan, Qin Li, Ning Li, Zhujing Qiu, Zhifeng Xiao, Fenghua Xu, Linling Lv, Minjia Chen, Senhong Ying, Lu Chen, Yuting Tian, Guanhu Li, Zhou Zhang, Mi He, Liang Qiao, Zhu Zhang, Dongfeng Chen, Qian Cao, Yongjian Nian, Yanling Wei |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Lecturer | 2 | 9% |
| Student > Bachelor | 2 | 9% |
| Student > Doctoral Student | 1 | 4% |
| Librarian | 1 | 4% |
| Professor | 1 | 4% |
| Other | 2 | 9% |
| Unknown | 14 | 61% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 17% |
| Computer Science | 2 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Business, Management and Accounting | 1 | 4% |
| Unknown | 15 | 65% |
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 19 March 2022.
All research outputs
#15,074,843
of 23,376,718 outputs
Outputs from Frontiers in Medicine
#2,874
of 5,991 outputs
Outputs of similar age
#246,734
of 468,983 outputs
Outputs of similar age from Frontiers in Medicine
#275
of 616 outputs
Altmetric has tracked 23,376,718 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 5,991 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has gotten more attention than average, scoring higher than 51% 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 468,983 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 616 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 54% of its contemporaries.