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Development of nomogram models of inflammatory markers based on clinical database to predict prognosis for hepatocellular carcinoma after surgical resection

Overview of attention for article published in BMC Cancer, March 2022
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Mentioned by

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1 X user

Citations

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15 Dimensions

Readers on

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11 Mendeley
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Title
Development of nomogram models of inflammatory markers based on clinical database to predict prognosis for hepatocellular carcinoma after surgical resection
Published in
BMC Cancer, March 2022
DOI 10.1186/s12885-022-09345-2
Pubmed ID
Authors

Shuqi Mao, Xi Yu, Jihan Sun, Yong Yang, Yuying Shan, Jiannan Sun, Joseph Mugaanyi, Rui Fan, Shengdong Wu, Caide Lu

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 9%
Other 1 9%
Student > Master 1 9%
Unknown 8 73%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 18%
Computer Science 1 9%
Medicine and Dentistry 1 9%
Unknown 7 64%
Attention Score in Context

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 April 2022.
All research outputs
#20,884,233
of 23,504,694 outputs
Outputs from BMC Cancer
#6,642
of 8,494 outputs
Outputs of similar age
#361,477
of 441,490 outputs
Outputs of similar age from BMC Cancer
#172
of 269 outputs
Altmetric has tracked 23,504,694 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,494 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 1st percentile – i.e., 1% 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 441,490 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 269 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.