Pruning Fuzzy Neural Network Applied to the Construction of Expert Systems to Aid in the Diagnosis of the Treatment of Cryotherapy and Immunotherapy
by
Augusto Junio Guimarães 1,†
, Paulo Vitor de Campos Souza 1,2,*,†, Vinícius Jonathan Silva Araújo 1, Thiago Silva Rezende 1 and Vanessa Souza Araújo 1
Augusto Junio Guimarães 1,†, Paulo Vitor de Campos Souza 1,2,*,†, Vinícius Jonathan Silva Araújo 1, Thiago Silva Rezende 1 and Vanessa Souza Araújo 1
1
Information Systems Course—Centro Universitário UNA de Betim, Betim 32600216, Brazil
2
Federal Center for Technological Education of Minas Gerais, Belo Horizonte 30421-169, Brazil
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Big Data Cogn. Comput. 2019, 3(2), 22; https://doi.org/10.3390/bdcc3020022
Received: 6 March 2019 / Revised: 25 March 2019 / Accepted: 3 April 2019 / Published: 9 April 2019
(This article belongs to the Special Issue Health Assessment in the Big Data Era)
Human papillomavirus (HPV) infection is related to frequent cases of cervical cancer and genital condyloma in humans. Up to now, numerous methods have come into existence for the prevention and treatment of this disease. In this context, this paper aims to help predict the susceptibility of the patient to forms treatment using both cryotherapy and immunotherapy. These studies facilitate the choice of medications, which can be painful and embarrassing for patients who have warts on intimate parts. However, the use of intelligent models generates efficient results but does not allow a better interpretation of the results. To solve the problem, we present the method of a fuzzy neural network (FNN). A hybrid model capable of solving complex problems and extracting knowledge from the database will pruned through F-score techniques to perform pattern classification in the treatment of warts, and to produce a specialist system based on if/then rules, according to the experience obtained from the database collected through medical research. Finally, binary pattern-classification tests realized in the FNN and compared with other models commonly used for classification tasks capture results of greater accuracy than the current state of the art for this type of problem (84.32% for immunotherapy, and 88.64% for cryotherapy), and extract fuzzy rules from the problem database. It was found that the hybrid approach based on neural networks and fuzzy systems can be an excellent tool to aid the prediction of cryotherapy and immunotherapy treatments.
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MDPI and ACS Style
Junio Guimarães, A.; Vitor de Campos Souza, P.; Jonathan Silva Araújo, V.; Silva Rezende, T.; Souza Araújo, V. Pruning Fuzzy Neural Network Applied to the Construction of Expert Systems to Aid in the Diagnosis of the Treatment of Cryotherapy and Immunotherapy. Big Data Cogn. Comput. 2019, 3, 22.
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