This paper is published in Volume-3, Issue-3, 2017
Area
Computer Science and Engineering
Author
Pawanpreet Kaur
Co-authors
Harshdeep Trehan, Varinderjit Kaur, Dr. Naveen Dhillon
Org/Univ
Ramgarhia Institute of Engineering & Technology, Phagwara, Punjab, India
Pub. Date
10 June, 2017
Paper ID
V3I3-1498
Publisher
Keywords
Parkinson’s Disease; Expert System; diseases; ANFIS; Neuro Fuzzy.

Citationsacebook

IEEE
Pawanpreet Kaur, Harshdeep Trehan, Varinderjit Kaur, Dr. Naveen Dhillon. Analysis of Adaptive Neuro–Fuzzy Based Expert System for Parkinson’s disease Diagnosis, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Pawanpreet Kaur, Harshdeep Trehan, Varinderjit Kaur, Dr. Naveen Dhillon (2017). Analysis of Adaptive Neuro–Fuzzy Based Expert System for Parkinson’s disease Diagnosis. International Journal of Advance Research, Ideas and Innovations in Technology, 3(3) www.IJARIIT.com.

MLA
Pawanpreet Kaur, Harshdeep Trehan, Varinderjit Kaur, Dr. Naveen Dhillon. "Analysis of Adaptive Neuro–Fuzzy Based Expert System for Parkinson’s disease Diagnosis." International Journal of Advance Research, Ideas and Innovations in Technology 3.3 (2017). www.IJARIIT.com.

Abstract

The real world Parkinson’s Disease(PD) is a chronic progressive neurological disease that affects a small area of nerve cells called neurons in the area of the brain called the substantia nigra. Medical Expert System technique is a solution of this problem. This paper summarizes regarding the classification of Parkinson’s disease by using adaptive neuro fuzzy inference engines. The learning focuses on diagnosis of P.D. by using adaptive neuro fuzzy inference system(ANFIS). The outcome obtained by fuzzy inference system is evaluated. MATLAB toolbox is designed for the simulation of the model. This also confirms that adaptive neuro is better option in which we use the symptoms of the patient which is suffering from Parkinson’s Disease and get a result.
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