Nature-inspired optimization of Type-2 fuzzy neural hybrid models for classification in medical diagnosis / Patricia Melin, Ivette Miramontes, German Prado Arechiga.
2022
R859.7.F89 M45 2022
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Title
Nature-inspired optimization of Type-2 fuzzy neural hybrid models for classification in medical diagnosis / Patricia Melin, Ivette Miramontes, German Prado Arechiga.
ISBN
9783030822194 (electronic bk.)
3030822192 (electronic bk.)
9783030822187
3030822184
3030822192 (electronic bk.)
9783030822187
3030822184
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource : illustrations (some color)
Item Number
10.1007/978-3-030-82219-4 doi
Call Number
R859.7.F89 M45 2022
Dewey Decimal Classification
610.1/511322
Summary
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.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed August 23, 2021).
Series
SpringerBriefs in applied sciences and technology. Computational intelligence. 2625-3704
Available in Other Form
Print version: 9783030822187
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