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Developing the novel diagnostic model and potential drugs by integrating bioinformatics and machine learning for aldosterone-producing adenomas

Overview of attention for article published in Frontiers in Molecular Biosciences, January 2024
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Title
Developing the novel diagnostic model and potential drugs by integrating bioinformatics and machine learning for aldosterone-producing adenomas
Published in
Frontiers in Molecular Biosciences, January 2024
DOI 10.3389/fmolb.2023.1308754
Pubmed ID
Authors

Deshui Yu, Jinxuan Zhang, Xintao Li, Shuwei Xiao, Jizhang Xing, Jianye Li

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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 1 100%
Readers by discipline Count As %
Medicine and Dentistry 1 100%
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 04 January 2024.
All research outputs
#22,502,430
of 25,104,329 outputs
Outputs from Frontiers in Molecular Biosciences
#3,008
of 4,601 outputs
Outputs of similar age
#130,924
of 162,456 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#48
of 81 outputs
Altmetric has tracked 25,104,329 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 4,601 research outputs from this source. They receive a mean Attention Score of 3.4. 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 162,456 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 81 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.