| 书目名称 | Nature-Inspired Methods for Smart Healthcare Systems and Medical Data | | 编辑 | Ahmed M. Anter,Mohamed Elhoseny,Anuradha D. Thakar | | 视频video | | | 概述 | Integrates nature-inspired algorithms into healthcare systems.Addresses medical data analytics using innovative optimization methods and IoT framework in real-time.Explores the potential of smart heal | | 图书封面 |  | | 描述 | .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 | | 出版日期 | Book 2024 | | 关键词 | Metaheuristics; Optimization, Internet of Things (IoT); Healthcare; Nature Inspired Methods; Data Mining | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-45952-8 | | isbn_softcover | 978-3-031-45954-2 | | isbn_ebook | 978-3-031-45952-8 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 19:03:10
