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Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2012
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Mentioned by

twitter
2 tweeters

Citations

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22 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
1 CiteULike
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Title
Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model
Published in
BMC Medical Informatics and Decision Making, June 2012
DOI 10.1186/1472-6947-12-54
Pubmed ID
Authors

Masahiro Takada, Masahiro Sugimoto, Yasuhiro Naito, Hyeong-Gon Moon, Wonshik Han, Dong-Young Noh, Masahide Kondo, Katsumasa Kuroi, Hironobu Sasano, Takashi Inamoto, Masaru Tomita, Masakazu Toi

Abstract

The aim of this study was to develop a new data-mining model to predict axillary lymph node (AxLN) metastasis in primary breast cancer. To achieve this, we used a decision tree-based prediction method-the alternating decision tree (ADTree).

Twitter Demographics

The data shown below were collected from the profiles of 2 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 4%
Unknown 44 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 30%
Student > Bachelor 5 11%
Student > Master 5 11%
Researcher 4 9%
Student > Postgraduate 4 9%
Other 12 26%
Unknown 2 4%
Readers by discipline Count As %
Medicine and Dentistry 8 17%
Computer Science 7 15%
Biochemistry, Genetics and Molecular Biology 6 13%
Engineering 5 11%
Nursing and Health Professions 4 9%
Other 12 26%
Unknown 4 9%

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 18 June 2012.
All research outputs
#2,283,650
of 4,508,612 outputs
Outputs from BMC Medical Informatics and Decision Making
#499
of 754 outputs
Outputs of similar age
#34,428
of 75,266 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#34
of 46 outputs
Altmetric has tracked 4,508,612 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 754 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 24th percentile – i.e., 24% 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 75,266 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.