Metaheuristics Algorithms For Medical Applications
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Metaheuristics Algorithms For Medical Applications
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Author : Mohamed Abdel-Basset
language : en
Publisher: Elsevier
Release Date : 2023-11-25
Metaheuristics Algorithms For Medical Applications written by Mohamed Abdel-Basset and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Computers categories.
Metaheuristics Algorithms for Medical Applications: Methods and Applications provides readers with the most complete reference for developing Metaheuristics techniques with Machine Learning for solving biomedical problems. The book is organized to present a stepwise progression beginning with the basics of Metaheuristics, leading into methods and practices, and concluding with advanced topics. The first section of the book presents the fundamental concepts of Metaheuristics and Machine Learning, and also provides a comprehensive taxonomic view of Metaheuristics methods according to a variety of criteria such as data type, scope, method, and so forth. The second section of the book explains how to apply Metaheuristics techniques for solving large-scale biomedical problems, including analysis and validation under different strategies. The final portion of the book focuses on advanced topics in Metaheuristics in four different applications. Readers will discover a variety of new methods, approaches, and techniques, as well as a wide range of applications demonstrating key concepts in Metaheuristics for biomedical science. The book provides a leading-edge resource for researchers in a variety of scientific fields who are interested in metaheuristics, including mathematics, biomedical engineering, computer science, biological sciences, and clinicians in medical practice. - Introduces a new set of Metaheuristics techniques for biomedical applications - Presents basic concepts of Metaheuristics, methods and practices, followed by advanced topics and applications - Provides researchers, practitioners, and project stakeholders with a complete guide for understanding and applying metaheuristics and machine learning techniques in their projects and solutions
Metaheuristics For Medicine And Biology
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Author : Amir Nakib
language : en
Publisher: Springer
Release Date : 2017-03-22
Metaheuristics For Medicine And Biology written by Amir Nakib and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-22 with Technology & Engineering categories.
This book highlights recent research on metaheuristics for biomedical engineering, addressing both theoretical and applications aspects. Given the multidisciplinary nature of bio-medical image analysis, it has now become one of the most central topics in computer science, computer engineering and electrical and electronic engineering, and attracted the interest of many researchers. To deal with these problems, many traditional and recent methods, algorithms and techniques have been proposed. Among them, metaheuristics is the most common choice. This book provides essential content for senior and young researchers interested in methodologies for implementing metaheuristics to help solve biomedical engineering problems.
Applications Of Hybrid Metaheuristic Algorithms For Image Processing
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Author : Diego Oliva
language : en
Publisher: Springer
Release Date : 2020-03-28
Applications Of Hybrid Metaheuristic Algorithms For Image Processing written by Diego Oliva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-28 with Technology & Engineering categories.
This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.
Metaheuristic Optimization Nature Inspired Algorithms Swarm And Computational Intelligence Theory And Applications
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Author : Modestus O. Okwu
language : en
Publisher: Springer Nature
Release Date : 2020-11-13
Metaheuristic Optimization Nature Inspired Algorithms Swarm And Computational Intelligence Theory And Applications written by Modestus O. Okwu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-13 with Technology & Engineering categories.
This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.
Advancements In Applied Metaheuristic Computing
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Author : Dey, Nilanjan
language : en
Publisher: IGI Global
Release Date : 2017-11-30
Advancements In Applied Metaheuristic Computing written by Dey, Nilanjan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Computers categories.
Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.
Nature Inspired Metaheuristic Algorithms
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Author : Sulabh Bansal
language : en
Publisher: CRC Press
Release Date : 2025-06-10
Nature Inspired Metaheuristic Algorithms written by Sulabh Bansal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-10 with Computers categories.
This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities. This book: Discusses load balancing and demand response using nature-inspired optimization techniques Presents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithms Covers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniques Explains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniques Illustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniques Nature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
Meta Heuristics Optimization Algorithms In Engineering Business Economics And Finance
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Author : Pandian Vasant
language : en
Publisher:
Release Date : 2013-01-01
Meta Heuristics Optimization Algorithms In Engineering Business Economics And Finance written by Pandian Vasant and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-01 with Heuristic algorithms categories.
"This book explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications"--
Next Generation Healthcare Informatics
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Author : B. K. Tripathy
language : en
Publisher: Springer Nature
Release Date : 2022-06-06
Next Generation Healthcare Informatics written by B. K. Tripathy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-06 with Technology & Engineering categories.
This edited book provides information on emerging fields of next-generation healthcare informatics with a special emphasis on emerging developments and applications of artificial intelligence, deep learning techniques, computational intelligence methods, Internet of medical things (IoMT), optimization techniques, decision making, nanomedicine, and cloud computing. The book provides a conceptual framework and roadmap for decision-makers for this transformation. The chapters involved in this book cover challenges and opportunities for diabetic retinopathy detection based on deep learning applications, deep learning accelerators in IoT and IoMT, health data analysis, deep reinforcement-based conversational AI agent in healthcare systems, examination of health data performance, multisource data in intelligent medicine, application of genetic algorithms in health care, mental disorder, digital healthcare system with big data analytics, encryption methods in healthcare data security, computation and cognitive bias in healthcare intelligence and pharmacogenomics, guided imagery therapy, cancer detection and prediction techniques, medical image processing for coronavirus, and imbalance learning in health care.
Iot And Ai Enabled Healthcare Solutions And Intelligent Disease Prediction
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Author : Bhoopesh Singh Bhati
language : en
Publisher: CRC Press
Release Date : 2025-09-09
Iot And Ai Enabled Healthcare Solutions And Intelligent Disease Prediction written by Bhoopesh Singh Bhati and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-09 with Computers categories.
The book presents fundamental to advanced concepts of AI and IoT in healthcare and disease prediction, demonstrating the emerging mechanisms, including machine learning, deep learning, image sensing, and explainable AI models to handle issues in healthcare industries with real-life scenarios. Included chapters are contributed by experienced professionals and academicians who examine severe diseases, applications, models, tools, frameworks, case studies, applications, and best practices in Healthcare. This book integrates the medical domain with AI technology. It covers trending explainable AI, computer vision (CV), and IoT that facilitate automation for healthcare solutions and medical diagnostics. The primary focus on explainable AI uncovers the black box of deep learning and bridges the distance between medical professionals and technologists. IoT in Healthcare: provides a mechanism of image sensing and is helpful in surgical tools.
Nature Inspired Methods For Smart Healthcare Systems And Medical Data
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Author : Ahmed M. Anter
language : en
Publisher: Springer Nature
Release Date : 2023-12-01
Nature Inspired Methods For Smart Healthcare Systems And Medical Data written by Ahmed M. Anter and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Medical categories.
This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry use. It explores the recent theoretical and practical applications of metaheuristics and optimization in various smart healthcare contexts. The book also discusses the capability of optimization techniques to obtain optimal parameters in ML and DL technologies. It provides an open platform for academics and engineers to share their unique ideas and investigate the potential convergence of existing systems and advanced metaheuristic algorithms. The book's outcome will enable decision-makers and practitioners to select suitable optimization approaches for scheduling patients in crowded environments with minimized human errors. The healthcare system aims to improve the lives of disabled, elderly, sick individuals, and children. IoT-based systems simplify decision-making and task automation, offering an automated foundation. Nature-inspired metaheuristics and mining algorithms are crucial for healthcare applications, reducing costs, increasing efficiency, enabling accurate data analysis, and enhancing patient care. Metaheuristics improve algorithm performance and address challenges in data mining and ML, making them essential in healthcare research. Real-time IoT-based healthcare systems can be modeled using an IoT-based metaheuristic approach to generate optimal solutions. Metaheuristics are powerful technologies for optimization problems in healthcare systems. They balance exact methods, which guarantee optimal solutions but require significant computational resources, with fast but low-quality greedy methods. Metaheuristic algorithms find better solutions while minimizing computational time. The scientific community is increasingly interested in metaheuristics, incorporating techniques from AI, operations research, and soft computing. New metaheuristicsoffer efficient ways to address optimization problems and tackle unsolved challenges. They can be parameterized to control performance and adjust the trade-off between solution quality and resource utilization. Metaheuristics manage the trade-off between performance and solution quality, making them highly applicable to real-time applications with pragmatic objectives.