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Computerized database management system for breast cancer patients

Overview of attention for article published in SpringerPlus, May 2014
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2 X users

Citations

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30 Mendeley
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Title
Computerized database management system for breast cancer patients
Published in
SpringerPlus, May 2014
DOI 10.1186/2193-1801-3-268
Pubmed ID
Authors

Kok Swee Sim, Sze Siang Chong, Chih Ping Tso, Mohsen Esmaeili Nia, Aun Kee Chong, Siti Fathimah Abbas

Abstract

Data analysis based on breast cancer risk factors such as age, race, breastfeeding, hormone replacement therapy, family history, and obesity was conducted on breast cancer patients using a new enhanced computerized database management system. My Structural Query Language (MySQL) is selected as the application for database management system to store the patient data collected from hospitals in Malaysia. An automatic calculation tool is embedded in this system to assist the data analysis. The results are plotted automatically and a user-friendly graphical user interface is developed that can control the MySQL database. Case studies show breast cancer incidence rate is highest among Malay women, followed by Chinese and Indian. The peak age for breast cancer incidence is from 50 to 59 years old. Results suggest that the chance of developing breast cancer is increased in older women, and reduced with breastfeeding practice. The weight status might affect the breast cancer risk differently. Additional studies are needed to confirm these findings.

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

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 20%
Student > Ph. D. Student 3 10%
Professor > Associate Professor 2 7%
Student > Master 2 7%
Other 1 3%
Other 4 13%
Unknown 12 40%
Readers by discipline Count As %
Computer Science 5 17%
Medicine and Dentistry 4 13%
Engineering 3 10%
Psychology 1 3%
Business, Management and Accounting 1 3%
Other 2 7%
Unknown 14 47%
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 29 May 2014.
All research outputs
#17,721,395
of 22,756,196 outputs
Outputs from SpringerPlus
#1,203
of 1,852 outputs
Outputs of similar age
#155,082
of 226,570 outputs
Outputs of similar age from SpringerPlus
#55
of 69 outputs
Altmetric has tracked 22,756,196 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 31st percentile – i.e., 31% 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 226,570 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.