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Pure tone audiogram classification using deep learning techniques

Overview of attention for article published in Clinical Otolaryngology & Allied Sciences, May 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users
peer_reviews
1 peer review site

Readers on

mendeley
3 Mendeley
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Title
Pure tone audiogram classification using deep learning techniques
Published in
Clinical Otolaryngology & Allied Sciences, May 2024
DOI 10.1111/coa.14170
Pubmed ID
Authors

Zhiyong Dou, Yingqiang Li, Dongzhou Deng, Yunxue Zhang, Anran Pang, Cong Fang, Xiang Bai, Dan Bing

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 67%
Student > Master 1 33%
Readers by discipline Count As %
Unspecified 2 67%
Business, Management and Accounting 1 33%
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 22 May 2024.
All research outputs
#16,144,501
of 25,980,896 outputs
Outputs from Clinical Otolaryngology & Allied Sciences
#683
of 1,653 outputs
Outputs of similar age
#77,812
of 183,610 outputs
Outputs of similar age from Clinical Otolaryngology & Allied Sciences
#7
of 23 outputs
Altmetric has tracked 25,980,896 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,653 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 55% 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 183,610 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.