Name
Title | ||
|---|---|---|
An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease |
Abstract | ||
|---|---|---|
Diabetes occurs when a body is unable to produce or respond properly to insulin which is needed to regulate glucose (sugar). Besides contributing to heart disease, diabetes also increases the risks of developing kidney disease, blindness, nerve damage, and blood vessel damage. In this paper, we have detected on diabetes disease, which is a very common and important disease using principal component analysis (PCA) and adaptive neuro-fuzzy inference system (ANFIS). The aim of this study is to improve the diagnostic accuracy of diabetes disease combining PCA and ANFIS. The proposed system has two stages. In the first stage, dimension of diabetes disease dataset that has 8 features is reduced to 4 features using principal component analysis. In the second stage, diagnosis of diabetes disease is conducted via adaptive neuro-fuzzy inference system classifier. We took the diabetes disease dataset used in our study from the UCI (from Department of Information and Computer Science, University of California) Machine Learning Database. The obtained classification accuracy of our system was 89.47% and it was very promising with regard to the other classification applications in literature for this problem. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.dsp.2006.09.005 | Digital Signal Processing |
Keywords | Field | DocType |
anfis,principal component analysis,heart disease,diabetes disease,diabetes disease dataset,kidney disease,classification accuracy,important disease,medical diagnosis,expert system approach,expert system,proposed system,adaptive neuro-fuzzy inference system,blood vessel damage,pca,machine learning,adaptive neuro fuzzy inference system | Diabetes mellitus,Disease,Pattern recognition,Expert system,Kidney disease,Artificial intelligence,Adaptive neuro fuzzy inference system,Principal component analysis,Machine learning,Mathematics,Medical diagnosis,Heart disease | Journal |
Volume | Issue | ISSN |
17 | 4 | Digital Signal Processing |
Citations | PageRank | References |
78 | 3.79 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kemal Polat | 1 | 1348 | 97.38 |
| Salih Güneş | 2 | 1267 | 78.53 |