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Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials

Overview of attention for article published in Cancer Medicine, July 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
21 Mendeley
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Title
Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials
Published in
Cancer Medicine, July 2022
DOI 10.1002/cam4.5060
Pubmed ID
Authors

Yougen Wu, Wenyu Zhu, Jing Wang, Lvwen Liu, Wei Zhang, Yang Wang, Jindong Shi, Ju Xia, Yuting Gu, Qingqing Qian, Yang Hong

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 14%
Student > Ph. D. Student 3 14%
Student > Bachelor 2 10%
Researcher 2 10%
Unspecified 1 5%
Other 1 5%
Unknown 9 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 10%
Medicine and Dentistry 2 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Unspecified 1 5%
Computer Science 1 5%
Other 3 14%
Unknown 11 52%
Attention Score in Context

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 27 July 2022.
All research outputs
#16,734,944
of 25,392,582 outputs
Outputs from Cancer Medicine
#1,691
of 3,924 outputs
Outputs of similar age
#237,139
of 433,363 outputs
Outputs of similar age from Cancer Medicine
#68
of 189 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,924 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 52% 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 433,363 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 189 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.