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Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up

Overview of attention for article published in Frontiers in endocrinology, September 2020
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1 X user

Citations

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25 Mendeley
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Title
Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up
Published in
Frontiers in endocrinology, September 2020
DOI 10.3389/fendo.2020.00643
Pubmed ID
Authors

Congxin Dai, Yanghua Fan, Yichao Li, Xinjie Bao, Yansheng Li, Mingliang Su, Yong Yao, Kan Deng, Bing Xing, Feng Feng, Ming Feng, Renzhi Wang

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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.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 16%
Student > Master 4 16%
Lecturer 2 8%
Student > Doctoral Student 2 8%
Professor > Associate Professor 2 8%
Other 3 12%
Unknown 8 32%
Readers by discipline Count As %
Medicine and Dentistry 8 32%
Engineering 2 8%
Computer Science 2 8%
Agricultural and Biological Sciences 2 8%
Environmental Science 1 4%
Other 2 8%
Unknown 8 32%
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 19 September 2020.
All research outputs
#23,487,873
of 26,163,973 outputs
Outputs from Frontiers in endocrinology
#8,673
of 13,370 outputs
Outputs of similar age
#362,782
of 418,809 outputs
Outputs of similar age from Frontiers in endocrinology
#226
of 327 outputs
Altmetric has tracked 26,163,973 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 13,370 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. 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 418,809 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 327 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.