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Entity recognition from clinical texts via recurrent neural network

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
112 Dimensions

Readers on

mendeley
189 Mendeley
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Title
Entity recognition from clinical texts via recurrent neural network
Published in
BMC Medical Informatics and Decision Making, July 2017
DOI 10.1186/s12911-017-0468-7
Pubmed ID
Authors

Zengjian Liu, Ming Yang, Xiaolong Wang, Qingcai Chen, Buzhou Tang, Zhe Wang, Hua Xu

Mendeley readers

The data shown below were compiled from readership statistics for 189 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 189 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 20%
Student > Master 31 16%
Researcher 22 12%
Student > Bachelor 15 8%
Student > Doctoral Student 14 7%
Other 31 16%
Unknown 39 21%
Readers by discipline Count As %
Computer Science 61 32%
Medicine and Dentistry 18 10%
Engineering 14 7%
Social Sciences 7 4%
Agricultural and Biological Sciences 7 4%
Other 28 15%
Unknown 54 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 05 September 2018.
All research outputs
#5,368,294
of 16,793,177 outputs
Outputs from BMC Medical Informatics and Decision Making
#611
of 1,525 outputs
Outputs of similar age
#62,235
of 161,987 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 16,793,177 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,525 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 57% 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 161,987 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 60% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them