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Detection of medical text semantic similarity based on convolutional neural network

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 2019
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
28 Mendeley
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Title
Detection of medical text semantic similarity based on convolutional neural network
Published in
BMC Medical Informatics and Decision Making, August 2019
DOI 10.1186/s12911-019-0880-2
Pubmed ID
Authors

Tao Zheng, Yimei Gao, Fei Wang, Chenhao Fan, Xingzhi Fu, Mei Li, Ya Zhang, Shaodian Zhang, Handong Ma

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 39%
Student > Bachelor 4 14%
Researcher 3 11%
Student > Ph. D. Student 3 11%
Other 2 7%
Other 2 7%
Unknown 3 11%
Readers by discipline Count As %
Computer Science 9 32%
Medicine and Dentistry 8 29%
Engineering 2 7%
Agricultural and Biological Sciences 1 4%
Nursing and Health Professions 1 4%
Other 3 11%
Unknown 4 14%

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 August 2019.
All research outputs
#13,786,585
of 15,625,110 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,324
of 1,416 outputs
Outputs of similar age
#218,840
of 262,407 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#3
of 6 outputs
Altmetric has tracked 15,625,110 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 1,416 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 262,407 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 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.