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Machine learning-based nomogram for distinguishing between supratentorial extraventricular ependymoma and supratentorial glioblastoma

Overview of attention for article published in Frontiers in oncology, September 2024
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Title
Machine learning-based nomogram for distinguishing between supratentorial extraventricular ependymoma and supratentorial glioblastoma
Published in
Frontiers in oncology, September 2024
DOI 10.3389/fonc.2024.1443913
Authors

Ling Chen, Weijiao Chen, Chuyun Tang, Yao Li, Min Wu, Lifang Tang, Lizhao Huang, Rui Li, Tao Li

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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 09 September 2024.
All research outputs
#23,918,279
of 26,623,241 outputs
Outputs from Frontiers in oncology
#16,920
of 23,393 outputs
Outputs of similar age
#113,097
of 145,349 outputs
Outputs of similar age from Frontiers in oncology
#65
of 318 outputs
Altmetric has tracked 26,623,241 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 23,393 research outputs from this source. They receive a mean Attention Score of 3.1. 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 145,349 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 318 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.