Risk Analysis of Diabetes Mellitus by Association Rule Summarization

Authors

  • Aishwarya Ingle  BE Scholar, Department of Computer Science and Engineering Rajiv Gandhi College of Engineering and Research, Nagpur, Maharashtra, India
  • Shivani Paraskar  BE Scholar, Department of Computer Science and Engineering Rajiv Gandhi College of Engineering and Research, Nagpur, Maharashtra, India
  • Avanti Ajane  BE Scholar, Department of Computer Science and Engineering Rajiv Gandhi College of Engineering and Research, Nagpur, Maharashtra, India
  • Sneha Mohadikar  BE Scholar, Department of Computer Science and Engineering Rajiv Gandhi College of Engineering and Research, Nagpur, Maharashtra, India
  • Lokesh Thota  BE Scholar, Department of Computer Science and Engineering Rajiv Gandhi College of Engineering and Research, Nagpur, Maharashtra, India
  • Prof. Ashwini Yerlekar  Assistant Professor, Department of Computer Science and Engineering Rajiv Gandhi College of Engineering and Research, Nagpur, Maharashtra, India

Keywords:

Diabetes Mellitus, Data mining, Association Rule Mining, Survival Analysis, Association Rule Summarization

Abstract

Early detection of patients with elevated risk of diabetes is very important in order that patients will begin to manage diabetes early and probably stop or delay the intense disease complications. By applying association rule mining to Electronic Medical Records (EMR), we intend to discover the set of risk factors and their respective collection that betokens the patients at particularly high risk of enrooting diabetes. We studied three association rule summarization technique and did a relative evaluation of these methodologies. We made use of these methodologies to find the fundamental segments which incite high risk of diabetes. All these three strategies made summations that portrayed sub masses at a high threat of diabetes with each system having its unmistakable quality. According to our inspiration, we use bottom up summarization (BUS) which conveys more fitting summary.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

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How to Cite

[1]
Aishwarya Ingle, Shivani Paraskar, Avanti Ajane, Sneha Mohadikar, Lokesh Thota, Prof. Ashwini Yerlekar, " Risk Analysis of Diabetes Mellitus by Association Rule Summarization" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp., March-April-2018.