Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/7765
Title: COMPARISM OF ADAPTIVE NEURO FUZZY INFERENCE SYSTEM AND SUPPORT VECTOR MACHINE FOR THE PREDICTION OF IMMUNOTHERAPY WARTS DISEASE
Authors: Abisoye, Blessing Olatunde
Abisoye, Opeyemi Aderiike
Kehinde, Lawal
Ogunwede, Emmanuel
Keywords: immunotherapy
warts
ANFIS
Support Vector Machine
Prediction
Classification
Issue Date: 24-Sep-2019
Publisher: 3rd International Engineering Conference (IEC 2019) Federal University of Technology, Minna, Nigeria
Abstract: Warts diseases are caused by virus within the Human Papilloma Virus Family (HPV). HPV are the cause of some types of cancer. Due to social stigma and the fact that warts never develop any symptoms until it full manifestation many patients seek medical treatment; The fast spread of warts disease due to skin-to-skin contact; Treatment are not cheap and simple, low number of treatment sessions and a lot of complications that do arise during the treatment seasons of warts disease; Lack of enough medical personals to treat warts disease cases and expert system to help the medical practitioners. To reduce the aforementioned problems, a machine learning approach of Adaptive Neuro Fuzzy Inference System (ANFIS) And Support Vector Machine (SVM) is proposed to predict Immunotherapy Warts Disease occurrence of before it gets out of hand. Performance comparism of ANFIS and SVM to the response of immunotherapy treatment of warts disease was conducted to get a good model. Selected features like age, type of warts, diameter of the warts, surface area of warts and the number of warts where considered as input variables. The accuracy of ANFIS and SVM models gave 69.697% and 96.29% respectively, the SVM model was considered to perform better than ANFIS in response to immunotherapy treatment of warts disease.
Description: Conference
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/7765
Appears in Collections:Computer Engineering

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