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A simulation model of colorectal cancer surveillance and recurrence

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2014
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Mentioned by

twitter
3 tweeters

Citations

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8 Dimensions

Readers on

mendeley
34 Mendeley
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Title
A simulation model of colorectal cancer surveillance and recurrence
Published in
BMC Medical Informatics and Decision Making, April 2014
DOI 10.1186/1472-6947-14-29
Pubmed ID
Authors

Johnie Rose, Knut Magne Augestad, Chung Yin Kong, Neal J Meropol, Michael W Kattan, Qingqing Hong, Xuebei An, Gregory S Cooper

Abstract

Approximately one-third of those treated curatively for colorectal cancer (CRC) will experience recurrence. No evidence-based consensus exists on how best to follow patients after initial treatment to detect asymptomatic recurrence. Here, a new approach for simulating surveillance and recurrence among CRC survivors is outlined, and development and calibration of a simple model applying this approach is described. The model's ability to predict outcomes for a group of patients under a specified surveillance strategy is validated.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Bangladesh 1 3%
Austria 1 3%
Unknown 32 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 29%
Researcher 7 21%
Student > Doctoral Student 3 9%
Professor > Associate Professor 3 9%
Librarian 2 6%
Other 7 21%
Unknown 2 6%
Readers by discipline Count As %
Medicine and Dentistry 19 56%
Engineering 2 6%
Agricultural and Biological Sciences 2 6%
Mathematics 1 3%
Nursing and Health Professions 1 3%
Other 6 18%
Unknown 3 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 2017.
All research outputs
#7,480,384
of 12,409,138 outputs
Outputs from BMC Medical Informatics and Decision Making
#743
of 1,122 outputs
Outputs of similar age
#93,162
of 193,386 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 12,409,138 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,122 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 30th percentile – i.e., 30% 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 193,386 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
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