Abstract
This research combines EM (Expectation maximization) Algorithm and C4.5 Algorithm together to build a type 2 diabetes data processing system. Taking the advantage of the nearly 14000 items of multi-source, multi-dimension practical dataset, and a series of data mining experiments are designed. With the large quantity of experiments and results analysis, some valuable pathological knowledge of type 2 diabetes was discovered, which includes, the decision tree is almost identical with the list of clinical diabetic risk factors, and the rate of correct recognition for healthy people was 80.9% while for diabetic patients was 92.05%; three new blood glucose threshold 5.85mmol/l, 5.26mmol/l and 4.28mmol/l, The valuable results are good to the cure and macro-control type 2 diabetes.
| Original language | English |
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| Title of host publication | 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007 |
| Pages | 371-377 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2007 |
| Event | 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007 - Beijing, China Duration: 23 May 2007 → 27 May 2007 |
Publication series
| Name | 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007 |
|---|
Conference
| Conference | 2007 IEEE/ICME International Conference on Complex Medical Engineering, CME 2007 |
|---|---|
| Country/Territory | China |
| City | Beijing |
| Period | 23/05/07 → 27/05/07 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Critical value
- EM Algorithm, C4.5 Algorithm
- Type 2 diabetes
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