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Rapid and simple colorimetric detection of multiple influenza viruses infecting humans using a reverse transcriptional loop-mediated isothermal amplification (RT-LAMP) diagnostic platform

Overview of attention for article published in BMC Infectious Diseases, August 2019
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
3 X users

Citations

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143 Dimensions

Readers on

mendeley
139 Mendeley
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Title
Rapid and simple colorimetric detection of multiple influenza viruses infecting humans using a reverse transcriptional loop-mediated isothermal amplification (RT-LAMP) diagnostic platform
Published in
BMC Infectious Diseases, August 2019
DOI 10.1186/s12879-019-4277-8
Pubmed ID
Authors

Su Jeong Ahn, Yun Hee Baek, Khristine Kaith S. Lloren, Won-Suk Choi, Ju Hwan Jeong, Khristine Joy C. Antigua, Hyeok-il Kwon, Su-Jin Park, Eun-Ha Kim, Young-il Kim, Young-Jae Si, Seung Bok Hong, Kyeong Seob Shin, Sungkun Chun, Young Ki Choi, Min-Suk Song

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 139 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 15%
Student > Ph. D. Student 19 14%
Student > Master 14 10%
Student > Bachelor 14 10%
Student > Doctoral Student 8 6%
Other 21 15%
Unknown 42 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 24%
Agricultural and Biological Sciences 17 12%
Engineering 6 4%
Medicine and Dentistry 6 4%
Immunology and Microbiology 4 3%
Other 23 17%
Unknown 50 36%
Attention Score in Context

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 12 April 2024.
All research outputs
#14,815,657
of 25,703,943 outputs
Outputs from BMC Infectious Diseases
#3,609
of 8,686 outputs
Outputs of similar age
#176,439
of 360,454 outputs
Outputs of similar age from BMC Infectious Diseases
#71
of 180 outputs
Altmetric has tracked 25,703,943 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,686 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. 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 360,454 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 50% of its contemporaries.
We're also able to compare this research output to 180 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.