Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10345657 | Computer Methods and Programs in Biomedicine | 2012 | 21 Pages |
Abstract
Classification is one of the key issues in medical diagnosis. In this paper, a novel approach to perform pattern classification tasks is presented. This model is called Associative Memory based Classifier (AMBC). Throughout the experimental phase, the proposed algorithm is applied to help diagnose diseases; particularly, it is applied in the diagnosis of seven different problems in the medical field. The performance of the proposed model is validated by comparing classification accuracy of AMBC against the performance achieved by other twenty well known algorithms. Experimental results have shown that AMBC achieved the best performance in three of the seven pattern classification problems in the medical field. Similarly, it should be noted that our proposal achieved the best classification accuracy averaged over all datasets.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Mario Aldape-Pérez, Cornelio Yáñez-Márquez, Oscar Camacho-Nieto, Amadeo J.Argüelles-Cruz,