Using Fuzzy Neural Networks to the Prediction of Improvement in Expert Systems for Treatment of Immunotherapy

Guimarães, Augusto Júnio; Araújo, Vinícius Jonathan Silva; Souza, Paulo Vitor de Campos; Araújo, Vanessa Souza; Rezende, Thiago Silva

doi:10.1007/978-3-030-03928-8_19

Cited by 20 publications

(22 citation statements)

References 17 publications

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“…Hybrid models also stand out in finding women with breast cancer [106,107] according to characteristics informed by patients by clinical trials. In the same way, it assists in the detection of an autistic trait in children [108] and immunotherapy treatment [109].…”

Section: Fuzzy Neural Network and Their Practical Applicationsmentioning

confidence: 99%

Detection of Anomalies in Large-Scale Cyberattacks Using Fuzzy Neural Networks

Souza

Guimarães

Rezende

et al. 2020

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The fuzzy neural networks are hybrid structures that can act in several contexts of the pattern classification, including the detection of failures and anomalous behaviors. This paper discusses the use of an artificial intelligence model based on the association between fuzzy logic and training of artificial neural networks to recognize anomalies in transactions involved in the context of computer networks and cyberattacks. In addition to verifying the accuracy of the model, fuzzy rules were obtained through knowledge from the massive datasets to form expert systems. The acquired rules allow the creation of intelligent systems in high-level languages with a robust level of identification of anomalies in Internet transactions, and the accuracy of the results of the test confirms that the fuzzy neural networks can act in anomaly detection in high-security attacks in computer networks.

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Section: Fuzzy Neural Network and Their Practical Applicationsmentioning

confidence: 99%

Detection of Anomalies in Large-Scale Cyberattacks Using Fuzzy Neural Networks

Souza

Guimarães

Rezende

et al. 2020

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“…In the work of [38] the focus was on the use of data mining techniques to help in the treatment of cancer with immunotherapy. Already in the works of [3,20]. the main focus was the construction of expert systems using decision trees and fuzzy neural networks respectively.…”

Section: Related Workmentioning

confidence: 99%

“…They effectively resolve problems of various types of science such as pattern classification [4][5][6][7][8], linear regression [9], time series forecasting [10], issues in industry [11], and also resolve problems in the areas of health [12][13][14][15][16][17] and software efforts [18,19]. Even problems in the field of immunotherapy have been the subject of judgment by these models in [20].…”

Section: Introductionmentioning

confidence: 99%

Pruning Fuzzy Neural Network Applied to the Construction of Expert Systems to Aid in the Diagnosis of the Treatment of Cryotherapy and Immunotherapy

Guimarães

Souza

Araújo

et al. 2019

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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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“…Finally, in the last decade, scientific work using such techniques has addressed detection of celestial materials (called Pulsars) [63]; prediction of autism in children [64], adolescents [65], and adults [66] through database obtained from mobile devices; breast cancer [67]; absenteeism at work [68]; control for active power filter [69,70]; data knowledge [71]; and speech recognition [72]. The diversity of these models also covers the field of predicting software building efforts [73], cybersecurity [74], help in cryotherapy and immunotherapy treatments [75,76], and different classification and regression problems [77][78][79][80][81][82][83], where the models differ according to the training techniques, fuzzification or defuzzification process, architecture, number of layers, elements present in the model structure, etc.…”

Section: Fuzzy Neural Networkmentioning

confidence: 99%

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

2019

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Featured Application: A hybrid model formed by neural network techniques and fuzzy systems that predicts rainfall and temperatures in the capital of Minas Gerais, Brazil, which contains several river sources essential for the Brazilian economy. The purpose of the paper is to construct a model capable of extracting knowledge from satellite data related to temperatures and rainfall forecast of the analyzed state.Abstract: The forecast for rainfall and temperatures in underdevelope countries can help in the definition of public and private investment strategies in preventive and corrective nature. Water is an essential element for the economy and living things. This study had a main objective to use an intelligent hybrid model capable of extracting fuzzy rules from a historical series of temperatures and rainfall indices of the state of Minas Gerais in Brazil, more specifically in the capital. Because this is state has several rivers fundamental to the Brazilian economy, this study intended to find knowledge in the data of the problem to help public managers and private investors to act dynamically in the prediction of future temperatures and how they can interfere in the decisions related to the population of the state. The results confirm that the intelligent hybrid model can act with efficiency in the generation of predictions about the temperatures and average rainfall indices, being an efficient tool to predict the water situation in the future of this critical state for Brazil. Appl. Sci. 2019, 9, 5476 2 of 30 watersheds critical nationally. Along with several great cities, it has suffered a strong impact from drought [4].In contrast to the lack of water, it has problems with excess: floods and landslides [2]. If a river or stream receives a considerable amount of water from rain and cannot support it, it ends up overflowing and causing floods, which bring with it destruction, damage, and even death.The facts cited above are just some of the impacts that rain has on society. Within this context, this work was developed for the use of neural networks in the forecast of volumetric rainfall, based on a fuzzy rule system, developing a precise forecast, and contributing to the anticipation of possible tragedies s in places that occur phenomena of greater magnitude, as well as helping in a better control of agriculture. Another purpose was to support air and sea transportation, avoiding accidents in their trajectories. Briefly, when anticipating a possible problem, it is also possible to anticipate solutions and reduce their impacts, such as evacuating areas at risk of landslides or flooding [5].Currently, many kinds of research are being developed to apply models of artificial neural networks in rain forecasts, river basins, and water studies. For example, it was applied to the problem of forecasting the flow of the Nile River in Egypt [6], using a temporal series as a reference to compare tests among several prediction methods of neural networks. Besides, there was a study using stochastic autoregressive mean m...

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Using Fuzzy Neural Networks to the Prediction of Improvement in Expert Systems for Treatment of Immunotherapy

Cited by 20 publications

References 17 publications

Detection of Anomalies in Large-Scale Cyberattacks Using Fuzzy Neural Networks

Detection of Anomalies in Large-Scale Cyberattacks Using Fuzzy Neural Networks

Pruning Fuzzy Neural Network Applied to the Construction of Expert Systems to Aid in the Diagnosis of the Treatment of Cryotherapy and Immunotherapy

Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites

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