The Research on Analyzing Risk Factors of Type 2 Diabetes Mellitus Based on Improved Frequent Pattern Tree Algorithm

DOI

10.2991/meita-15.2015.83How to use a DOI?

Keywords

data mining; Apriori Algorithm; Association rules; FP-tree Algorithm

Abstract

urpose: We do it to improve the low efficiency in analyzing risk factors of type 2 Diabetes Mellitus by Apriori Algorithm. Method: We use the patients’ data from the information department of one tertiary referral hospital in Lanzhou which include course note of disease and their health record form January 2009 to March 2014.We find out that the improved FP-tree Algorithm analyzes risk factors of type 2 diabetes better. And we analyze the efficiency by programming improved FP-tree and Apriori Algorithm with C# .Result: We can analyze the chart of time and number of records, time and support degree, main risk factors. Conclusion: The improved FP-tree Algorithm can be used to analyze the risk factors of Diabetes Mellitus and holds a higher efficiency.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhe Wei
AU  - Guangjian Ye
PY  - 2015/08
DA  - 2015/08
TI  - The Research on Analyzing Risk Factors of Type 2 Diabetes Mellitus Based on Improved Frequent Pattern Tree Algorithm
BT  - Proceedings of the 2015 International Conference on Materials Engineering and Information Technology Applications
PB  - Atlantis Press
SP  - 459
EP  - 463
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-15.2015.83
DO  - 10.2991/meita-15.2015.83
ID  - Wei2015/08
ER  -