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
Mohamed Abdel-Basset & Mohamed Elhoseny
Metaheuristics Algorithms for Medical Applications [EPUB ebook]
Methods and Applications
Metaheuristics Algorithms for Medical Applications [EPUB ebook]
Methods and Applications
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Limba Engleză ● Format EPUB ● ISBN 9780443133152 ● Editura Elsevier Science ● Publicat 2023 ● Descărcabil 3 ori ● Valută EUR ● ID 9275243 ● Protecție împotriva copiilor Adobe DRM
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