Neuro Fuzzy Hybrid Models For Classification In Medical Diagnosis

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Neuro Fuzzy Hybrid Models For Classification In Medical Diagnosis

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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2020-10-27

Neuro Fuzzy Hybrid Models For Classification In Medical Diagnosis written by Patricia Melin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-27 with Technology & Engineering categories.

This book is focused on the use of intelligent techniques, such as fuzzy logic, neural networks and bio-inspired algorithms, and their application in medical diagnosis. The main idea is that the proposed method may be able to adapt to medical diagnosis problems in different possible areas of the medicine and help to have an improvement in diagnosis accuracy considering a clinical monitoring of 24 hours or more of the patient. In this book, tests were made with different architectures proposed in the different modules of the proposed model. First, it was possible to obtain the architecture of the fuzzy classifiers for the level of blood pressure and for the pressure load, and these were optimized with the different bio-inspired algorithms (Genetic Algorithm and Chicken Swarm Optimization). Secondly, we tested with a local database of 300 patients and good results were obtained. It is worth mentioning that this book is an important part of the proposed general model; for this reason, we consider that these modules have a good performance in a particular way, but it is advisable to perform more tests once the general model is completed.

New Hybrid Intelligent Systems For Diagnosis And Risk Evaluation Of Arterial Hypertension

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Author : Patricia Melin
language : en
Publisher: Springer
Release Date : 2017-07-04

New Hybrid Intelligent Systems For Diagnosis And Risk Evaluation Of Arterial Hypertension written by Patricia Melin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-04 with Technology & Engineering categories.

In this book, a new approach for diagnosis and risk evaluation of ar-terial hypertension is introduced. The new approach was implement-ed as a hybrid intelligent system combining modular neural net-works and fuzzy systems. The different responses of the hybrid system are combined using fuzzy logic. Finally, two genetic algo-rithms are used to perform the optimization of the modular neural networks parameters and fuzzy inference system parameters. The experimental results obtained using the proposed method on real pa-tient data show that when the optimization is used, the results can be better than without optimization. This book is intended to be a refer-ence for scientists and physicians interested in applying soft compu-ting techniques, such as neural networks, fuzzy logic and genetic algorithms, in medical diagnosis, but also in general to classification and pattern recognition and similar problems.

Nature Inspired Optimization Of Type 2 Fuzzy Neural Hybrid Models For Classification In Medical Diagnosis

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Author : Patricia Melin
language : en
Publisher:
Release Date : 2022

Nature Inspired Optimization Of Type 2 Fuzzy Neural Hybrid Models For Classification In Medical Diagnosis written by Patricia Melin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.

This book describes the utilization of different soft computing techniques and their optimization for providing an accurate and efficient medical diagnosis. The proposed method provides a precise and timely diagnosis of the risk that a person has to develop a particular disease, but it can be adaptable to provide the diagnosis of different diseases. This book reflects the experimentation that was carried out, based on the different optimizations using bio-inspired algorithms (such as bird swarm algorithm, flower pollination algorithms, and others). In particular, the optimizations were carried out to design the fuzzy classifiers of the nocturnal blood pressure profile and heart rate level. In addition, to obtain the architecture that provides the best result, the neurons and the number of neurons per layers of the artificial neural networks used in the model are optimized. Furthermore, different tests were carried out with the complete optimized model. Another work that is presented in this book is the dynamic parameter adaptation of the bird swarm algorithm using fuzzy inference systems, with the aim of improving its performance. For this, different experiments are carried out, where mathematical functions and a monolithic neural network are optimized to compare the results obtained with the original algorithm. The book will be of interest for graduate students of engineering and medicine, as well as researchers and professors aiming at proposing and developing new intelligent models for medical diagnosis. In addition, it also will be of interest for people working on metaheuristic algorithms and their applications on medicine.

Advanced Classification Techniques For Healthcare Analysis

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Author : Chakraborty, Chinmay
language : en
Publisher: IGI Global
Release Date : 2019-02-22

Advanced Classification Techniques For Healthcare Analysis written by Chakraborty, Chinmay and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-22 with Medical categories.

Medical and information communication technology professionals are working to develop robust classification techniques, especially in healthcare data/image analysis, to ensure quick diagnoses and treatments to patients. Without fast and immediate access to healthcare databases and information, medical professionals’ success rates and treatment options become limited and fall to disastrous levels. Advanced Classification Techniques for Healthcare Analysis provides emerging insight into classification techniques in delivering quality, accurate, and affordable healthcare, while also discussing the impact health data has on medical treatments. Featuring coverage on a broad range of topics such as early diagnosis, brain-computer interface, metaheuristic algorithms, clustering techniques, learning schemes, and mobile telemedicine, this book is ideal for medical professionals, healthcare administrators, engineers, researchers, academicians, and technology developers seeking current research on furthering information and communication technology that improves patient care.

Intuitionistic And Type 2 Fuzzy Logic Enhancements In Neural And Optimization Algorithms Theory And Applications

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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2020-02-27

Intuitionistic And Type 2 Fuzzy Logic Enhancements In Neural And Optimization Algorithms Theory And Applications written by Oscar Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-27 with Technology & Engineering categories.

This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.

Nature Inspired Optimization Of Type 2 Fuzzy Neural Hybrid Models For Classification In Medical Diagnosis

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Author : Patricia Melin
language : en
Publisher: Springer Nature
Release Date : 2021-08-06

Nature Inspired Optimization Of Type 2 Fuzzy Neural Hybrid Models For Classification In Medical Diagnosis written by Patricia Melin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-06 with Technology & Engineering categories.

This book describes the utilization of different soft computing techniques and their optimization for providing an accurate and efficient medical diagnosis. The proposed method provides a precise and timely diagnosis of the risk that a person has to develop a particular disease, but it can be adaptable to provide the diagnosis of different diseases. This book reflects the experimentation that was carried out, based on the different optimizations using bio-inspired algorithms (such as bird swarm algorithm, flower pollination algorithms, and others). In particular, the optimizations were carried out to design the fuzzy classifiers of the nocturnal blood pressure profile and heart rate level. In addition, to obtain the architecture that provides the best result, the neurons and the number of neurons per layers of the artificial neural networks used in the model are optimized. Furthermore, different tests were carried out with the complete optimized model. Another work that is presented in this book is the dynamic parameter adaptation of the bird swarm algorithm using fuzzy inference systems, with the aim of improving its performance. For this, different experiments are carried out, where mathematical functions and a monolithic neural network are optimized to compare the results obtained with the original algorithm. The book will be of interest for graduate students of engineering and medicine, as well as researchers and professors aiming at proposing and developing new intelligent models for medical diagnosis. In addition, it also will be of interest for people working on metaheuristic algorithms and their applications on medicine.

Study Of Early Prediction And Classification Of Arthritis Disease Using Soft Computing Techniques

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Author : S. Shanmugam
language : en
Publisher: Infinite Study
Release Date :

Study Of Early Prediction And Classification Of Arthritis Disease Using Soft Computing Techniques written by S. Shanmugam and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.

Arthritis is the most familiar element of disability in the World. At a rate of 20 million people in the US are suffering from Arthritis. It characterizes around 200 rheumatic diseases and conditions that influence joints. The tissues surround the joint, and other connective tissue.

Nature Inspired Design Of Hybrid Intelligent Systems

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Author : Patricia Melin
language : en
Publisher: Springer
Release Date : 2016-12-08

Nature Inspired Design Of Hybrid Intelligent Systems written by Patricia Melin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-08 with Technology & Engineering categories.

This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

Accuracy Of Rule Extraction Using A Recursive Rule Extraction Algorithm With Continuous Attributes Combined With A Sampling Selection Technique For The Diagnosis Of Liver Disease

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Author : Yoichi Hayashi
language : en
Publisher: Infinite Study
Release Date :

Accuracy Of Rule Extraction Using A Recursive Rule Extraction Algorithm With Continuous Attributes Combined With A Sampling Selection Technique For The Diagnosis Of Liver Disease written by Yoichi Hayashi and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.

Although liver cancer is the second most common cause of death from cancer worldwide, because of the limited accuracy and interpretability of extracted classification rules, the diagnosis of liver disease remains difficult. In addition, hepatitis, which is inflammation of the liver, can progress to fibrosis, cirrhosis, or even liver cancer.

Medical Diagnosis Using Artificial Neural Networks

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Author : Moein, Sara
language : en
Publisher: IGI Global
Release Date : 2014-06-30

Medical Diagnosis Using Artificial Neural Networks written by Moein, Sara and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-30 with Medical categories.

Advanced conceptual modeling techniques serve as a powerful tool for those in the medical field by increasing the accuracy and efficiency of the diagnostic process. The application of artificial intelligence assists medical professionals to analyze and comprehend a broad range of medical data, thus eliminating the potential for human error. Medical Diagnosis Using Artificial Neural Networks introduces effective parameters for improving the performance and application of machine learning and pattern recognition techniques to facilitate medical processes. This book is an essential reference work for academicians, professionals, researchers, and students interested in the relationship between artificial intelligence and medical science through the use of informatics to improve the quality of medical care.