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An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice

Overview of attention for article published in International Journal of Medical Informatics, February 2023
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Mentioned by

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1 X user

Citations

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1 Dimensions

Readers on

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10 Mendeley
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Title
An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice
Published in
International Journal of Medical Informatics, February 2023
DOI 10.1016/j.ijmedinf.2023.105021
Pubmed ID
Authors

Carol El-Hayek, Siamak Barzegar, Noel Faux, Kim Doyle, Priyanka Pillai, Simon J Mutch, Alaina Vaisey, Roger Ward, Lena Sanci, Adam G Dunn, Margaret E Hellard, Jane S Hocking, Karin Verspoor, Douglas Ir Boyle

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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 10%
Professor > Associate Professor 1 10%
Researcher 1 10%
Lecturer 1 10%
Unknown 6 60%
Readers by discipline Count As %
Computer Science 2 20%
Business, Management and Accounting 1 10%
Engineering 1 10%
Unknown 6 60%
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 05 March 2023.
All research outputs
#22,778,604
of 25,394,764 outputs
Outputs from International Journal of Medical Informatics
#1,716
of 1,865 outputs
Outputs of similar age
#413,449
of 482,546 outputs
Outputs of similar age from International Journal of Medical Informatics
#25
of 29 outputs
Altmetric has tracked 25,394,764 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 1,865 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 482,546 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 29 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.