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ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
2 X users
patent
1 patent
wikipedia
1 Wikipedia page

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
57 Mendeley
citeulike
1 CiteULike
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Title
ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials
Published in
BMC Medical Informatics and Decision Making, April 2012
DOI 10.1186/1472-6947-12-s1-s3
Pubmed ID
Authors

Ioannis Korkontzelos, Tingting Mu, Sophia Ananiadou

Abstract

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Portugal 1 2%
United Kingdom 1 2%
United Arab Emirates 1 2%
Taiwan 1 2%
Canada 1 2%
Unknown 50 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 21%
Researcher 9 16%
Student > Master 8 14%
Student > Doctoral Student 4 7%
Other 4 7%
Other 12 21%
Unknown 8 14%
Readers by discipline Count As %
Computer Science 16 28%
Medicine and Dentistry 13 23%
Agricultural and Biological Sciences 5 9%
Nursing and Health Professions 2 4%
Decision Sciences 2 4%
Other 9 16%
Unknown 10 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 17 January 2023.
All research outputs
#4,349,370
of 23,549,388 outputs
Outputs from BMC Medical Informatics and Decision Making
#381
of 2,028 outputs
Outputs of similar age
#28,713
of 164,090 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#8
of 40 outputs
Altmetric has tracked 23,549,388 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,028 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 80% 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 164,090 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.