Title :
Automatic Diagnosis of Asthma Using Neurofuzzy System
Author :
Ansari, A.Q. ; Gupta, Neeraj K. ; Ekata, E.
Author_Institution :
Dept. of Electr. Eng., Jamia Millia Islamia, New Delhi, India
Abstract :
In this paper, automatic diagnosis of asthma usingneurofuzzy approaches are presented. Adaptive Neural Fuzzy Inference System(ANFIS) is put in the framework of adaptive systems to facilitate learning and adaptation which uses back propagation algorithm to reduce the error in the output. In first phase input variables are prepared by taking a healthy person as a reference and in second phase these inputs with asthma patient are given to ANFIS to obtain output. Simulated result shows the proposed work for automated diagnosis, which have performed by using the realistic causes of asthma disease are effective.
Keywords :
backpropagation; diseases; fuzzy reasoning; medical computing; neural nets; patient diagnosis; ANFIS; adaptive neural fuzzy inference system; asthma disease; asthma patient; automatic asthma diagnosis; back propagation algorithm; learning; neurofuzzy system; Adaptive systems; Computer architecture; Input variables; Medical diagnostic imaging; Medical services; Neural networks; Training; Asthma; Backpropagation; Neurofuzzy system;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on
Conference_Location :
Mathura
Print_ISBN :
978-1-4673-2981-1
DOI :
10.1109/CICN.2012.55