Application of an Improved Attribute Reduction Algorithm in Diabetic Complication Diagnosis

Ju Li; Bei Zhou; Xing Wang; Wei Zhang; Jie Wen

doi:10.4028/www.scientific.net/AMR.267.1048

Paper Titles

The Data Acquisition, Process and Reconstruction for a Reverse Engineering Study
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Efficient Mobile Anchor Point Messaging Assumption in IPv6 Based Wireless Mobile Networks
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Office System Design and Implementation Based on B/S
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Application of an Improved Attribute Reduction Algorithm in Diabetic Complication Diagnosis
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A Co-Training Based Semi-Supervised Human Action Recognition Algorithm
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 267Application of an Improved Attribute Reduction...

Application of an Improved Attribute Reduction Algorithm in Diabetic Complication Diagnosis

Abstract:

At present, people of several major diseases that threaten human diagnosis and treatment is extremely limited, including diabetes and its complications. These diseases a great deal of pain and heavy burden to human beings. For early detection, early treatment, this paper constructed a prediction model of diabetic complications using rough set and developed a CAD system, the experiments show that the proposed rule extraction method is feasible and effective.

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Periodical:

Advanced Materials Research (Volume 267)

Pages:

1048-1050

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.267.1048

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Online since:

June 2011

Authors:

Ju Li, Bei Zhou, Xing Wang, Wei Zhang, Jie Wen

Keywords:

Diabetic Complication, Prediction Model, Rough Set (RS)

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References

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DOI: 10.1007/978-94-015-7975-9_27

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