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 |
Liver imaging features by convolutional neural network to predict the metachronous liver metastasis in stage I-III colorectal cancer patients based on preoperative abdominal CT scan
|
---|---|
Published in |
BMC Bioinformatics, September 2020
|
DOI | 10.1186/s12859-020-03686-0 |
Pubmed ID | |
Authors |
Sangwoo Lee, Eun Kyung Choe, So Yeon Kim, Hua Sun Kim, Kyu Joo Park, Dokyoon Kim |
X Demographics
The data shown below were collected from the profiles of 12 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 | 3 | 25% |
South Africa | 1 | 8% |
Spain | 1 | 8% |
Mexico | 1 | 8% |
India | 1 | 8% |
Netherlands | 1 | 8% |
Unknown | 4 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 67% |
Scientists | 3 | 25% |
Practitioners (doctors, other healthcare professionals) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 63 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 9 | 14% |
Student > Master | 7 | 11% |
Student > Ph. D. Student | 5 | 8% |
Lecturer | 5 | 8% |
Other | 4 | 6% |
Other | 13 | 21% |
Unknown | 20 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 10 | 16% |
Computer Science | 8 | 13% |
Engineering | 5 | 8% |
Psychology | 4 | 6% |
Chemistry | 3 | 5% |
Other | 9 | 14% |
Unknown | 24 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 17 January 2021.
All research outputs
#4,759,819
of 23,511,526 outputs
Outputs from BMC Bioinformatics
#1,784
of 7,405 outputs
Outputs of similar age
#115,069
of 408,936 outputs
Outputs of similar age from BMC Bioinformatics
#48
of 149 outputs
Altmetric has tracked 23,511,526 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,405 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 75% 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 408,936 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 149 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 68% of its contemporaries.