You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning Model for Predicting the Pathological Complete Response to Neoadjuvant Chemoradiotherapy of Locally Advanced Rectal Cancer
|
|---|---|
| Published in |
Frontiers in oncology, June 2022
|
| DOI | 10.3389/fonc.2022.807264 |
| Pubmed ID | |
| Authors |
Xiaoying Lou, Niyun Zhou, Lili Feng, Zhenhui Li, Yuqi Fang, Xinjuan Fan, Yihong Ling, Hailing Liu, Xuan Zou, Jing Wang, Junzhou Huang, Jingping Yun, Jianhua Yao, Yan Huang |
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 States | 2 | 50% |
| Switzerland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 4 | 15% |
| Researcher | 2 | 7% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Other | 1 | 4% |
| Student > Master | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 15 | 56% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 4 | 15% |
| Medicine and Dentistry | 3 | 11% |
| Computer Science | 3 | 11% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Unknown | 16 | 59% |
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 27 June 2022.
All research outputs
#17,881,371
of 26,178,577 outputs
Outputs from Frontiers in oncology
#8,278
of 22,922 outputs
Outputs of similar age
#269,669
of 452,791 outputs
Outputs of similar age from Frontiers in oncology
#583
of 1,692 outputs
Altmetric has tracked 26,178,577 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 22,922 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 58% 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 452,791 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,692 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 61% of its contemporaries.