Name
Title | ||
|---|---|---|
Automatic detection of heart disease using an artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism and k |
Abstract | ||
|---|---|---|
It is evident that usage of machine learning methods in disease diagnosis has been increasing gradually. In this study, diagnosis of heart disease, which is a very common and important disease, was conducted with such a machine learning system. In this system, a new weighting scheme based on k-nearest neighbour (k-nn) method was utilized as a preprocessing step before the main classifier. Artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism was our used classifier. We took the dataset used in our study from the UCI Machine Learning Database. The obtained classification accuracy of our system was 87% and it was very promising with regard to the other classification applications in the literature for this problem. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.eswa.2006.01.027 | Expert Systems with Applications |
Keywords | Field | DocType |
Heart disease,Artificial immune system,AIRS,k-nn based weighting preprocessing,Expert systems | Data mining,Nearest neighbour,Weighting,Computer science,Artificial intelligence,Classifier (linguistics),Artificial immune system,Pattern recognition,Expert system,Fuzzy logic,Preprocessor,Resource allocation,Machine learning | Journal |
Volume | Issue | ISSN |
32 | 2 | 0957-4174 |
Citations | PageRank | References |
4 | 0.40 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kemal Polat | 1 | 1348 | 97.38 |
| Seral Şahan | 2 | 210 | 17.86 |
| Salih Güneş | 3 | 1267 | 78.53 |