Soft computing in medical diagnostic applications: A short review

Author

Al-Absi, Hamada R H ; Abdullah, Azween ; Hassan, Mahamat Issa

Author_Institution

Dept. of Comput. & Inf. Sci., Univ. Teknol. PETRONAS, Tronoh, Malaysia

fYear

2011

fDate

19-20 Sept. 2011

Firstpage

1

Lastpage

5

Abstract

Medical diagnosis is one of the most important issues in healthcare. Computer aided systems have been developed in order to diagnose diseases by examining the internal human organs through medical images captured by MRI, CT scan etc. Many techniques have been utilized in order to develop these systems. In this paper, a short review on artificial neural network, fuzzy logic and genetic algorithm techniques in medical diagnostic applications is presented. The purpose of this review is to select the most suitable soft computing methodology to build a disease diagnosis system with high capabilities. The combination of artificial neural network, fuzzy logic and genetic algorithm in one methodology was reported to have a great advantage in producing systems with better performance.

Keywords

biomedical MRI; computerised tomography; diseases; fuzzy logic; genetic algorithms; medical image processing; neural nets; patient diagnosis; CT scan; MRI; artificial neural network; computer aided systems; disease diagnosis system; fuzzy logic; genetic algorithm techniques; internal human organs; medical diagnostic applications; medical images; soft computing; Accuracy; Artificial neural networks; Computers; Fuzzy logic; Genetic algorithms; Medical diagnostic imaging; Artificial Neural network; Computer aided diagnosis; Fuzzy Logic; Genetic Algorithm; Soft computing;

fLanguage

English

Publisher

ieee

Conference_Titel

National Postgraduate Conference (NPC), 2011

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4577-1882-3

Type

conf

DOI

10.1109/NatPC.2011.6136288

Filename

6136288