Téléchargez le livre : Nature-Inspired Methods for Smart Healthcare Systems and Medical Data

Nature-Inspired Methods for Smart Healthcare Systems and Medical Data

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Springer


Paru le : 2023-12-01

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Description

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.
Pages
250 pages
Collection
n.c
Parution
2023-12-01
Marque
Springer
EAN papier
9783031459511
EAN PDF
9783031459528
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
14172 Ko
Prix
158,24 €
EAN EPUB
9783031459528
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
25754 Ko
Prix
158,24 €

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