Title
Medical Diagnosis of Chronic Diseases Based on a Novel Computational Intelligence Algorithm.
Abstract
Computational Intelligence techniques in medicine have become an increasing area of research worldwide. Among them, the application and development of new models and algorithms for disease diagnosis and prediction have been an active research topic. The research contribution of the current paper is the proposal of a novel classification model, and its application to the diagnosis of chronic diseases. One of the main characteristics of the new model is that it is designed to deal with imbalanced data. With the purpose of making experimental comparisons to demonstrate the benefits of the proposed model, we tested five classification models, over medical data. The application of the supervised classification algorithms is done over the Knowledge Extraction based on Evolutionary Learning (KEEL) environment, using a distributed optimally balanced stratified 5-fold cross validation scheme. In addition, the experimental results obtained were validated in order to identify significant differences in performance by mean of a non-parametric statistical test (the Friedman test), and a post-hoc test (the Holm test). The hypothesis testing analysis of the experimental results indicates that the proposed model outperforms other supervised classifiers for medical diagnosis.
Year
Venue
Keywords
2018
JOURNAL OF UNIVERSAL COMPUTER SCIENCE
medical informatics,disease prediction and diagnosis,computational intelligence
Field
DocType
Volume
Data mining,Computational intelligence,Computer science,Artificial intelligence,Medical diagnosis,Machine learning
Journal
24
Issue
ISSN
Citations 
6
0948-695X
0
PageRank 
References 
Authors
0.34
0
5