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New threats to health data privacy

Overview of attention for article published in BMC Bioinformatics, November 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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7 X users

Citations

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28 Dimensions

Readers on

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122 Mendeley
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Title
New threats to health data privacy
Published in
BMC Bioinformatics, November 2011
DOI 10.1186/1471-2105-12-s12-s7
Pubmed ID
Authors

Fengjun Li, Xukai Zou, Peng Liu, Jake Y Chen

Abstract

Along with the rapid digitalization of health data (e.g. Electronic Health Records), there is an increasing concern on maintaining data privacy while garnering the benefits, especially when the data are required to be published for secondary use. Most of the current research on protecting health data privacy is centered around data de-identification and data anonymization, which removes the identifiable information from the published health data to prevent an adversary from reasoning about the privacy of the patients. However, published health data is not the only source that the adversaries can count on: with a large amount of information that people voluntarily share on the Web, sophisticated attacks that join disparate information pieces from multiple sources against health data privacy become practical. Limited efforts have been devoted to studying these attacks yet.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
United States 2 2%
Canada 2 2%
France 1 <1%
Germany 1 <1%
Malaysia 1 <1%
Unknown 113 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 23 19%
Student > Ph. D. Student 15 12%
Student > Bachelor 14 11%
Researcher 11 9%
Other 7 6%
Other 20 16%
Unknown 32 26%
Readers by discipline Count As %
Computer Science 31 25%
Medicine and Dentistry 15 12%
Social Sciences 10 8%
Business, Management and Accounting 6 5%
Agricultural and Biological Sciences 5 4%
Other 18 15%
Unknown 37 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 13 April 2018.
All research outputs
#6,911,687
of 23,306,612 outputs
Outputs from BMC Bioinformatics
#2,614
of 7,380 outputs
Outputs of similar age
#62,510
of 242,217 outputs
Outputs of similar age from BMC Bioinformatics
#54
of 111 outputs
Altmetric has tracked 23,306,612 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,380 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 64% 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 242,217 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 74% of its contemporaries.
We're also able to compare this research output to 111 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 51% of its contemporaries.