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OverviewThis book introduces a variety of well-proven and newly developed nature-inspired optimization algorithms solving a wide range of real-life biomedical and healthcare problems. Few solo and hybrid approaches are demonstrated in a lucid manner for the effective integration and finding solution for a large-scale complex healthcare problem. In the present bigdata-based computing scenario, nature-inspired optimization techniques present adaptive mechanisms that permit the understanding of complex data and altering environments. This book is a voluminous collection for the confront faced by the healthcare institutions and hospitals for practical analysis, storage, and data analysis. It explores the distinct nature-inspired optimization-based approaches that are able to handle more accurate outcomes for the current biomedical and healthcare problems. In addition to providing a state-of-the-art and advanced intelligent methods, it also enlightens an insight for solving diversified healthcare problems such as cancer and diabetes. Full Product DetailsAuthor: Janmenjoy Nayak , Asit Kumar Das , Bighnaraj Naik , Saroj K. MeherPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 2023 ed. Volume: 233 Weight: 0.635kg ISBN: 9783031175435ISBN 10: 3031175433 Pages: 293 Publication Date: 15 November 2022 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsNature-Inspired Optimization Algorithms: Past to Present.- Preventing the early spread of infectious diseases using Particle Swarm Optimization.- Optimized gradient boosting tree-based model for obesity level prediction from patient’s physical condition and eating habits.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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