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Nature-inspired optimization methodologies in biomedical and healthcare

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nature-inspired optimization methodologies in biomedical and healthcareedited by Janmenjoy Nayak ... [et al.].
other author:	Nayak, Janmenjoy.
Published:	Cham :Springer International Publishing :2023.
Description:	xviii, 293 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Mathematical optimization.
Online resource:	https://doi.org/10.1007/978-3-031-17544-2
ISBN:	9783031175442$q(electronic bk.)

Nature-inspired optimization methodologies in biomedical and healthcare
Nature-inspired optimization methodologies in biomedical and healthcare[electronic resource] /edited by Janmenjoy Nayak ... [et al.]. - Cham :Springer International Publishing :2023. - xviii, 293 p. :ill., digital ;24 cm. - Intelligent systems reference library,v. 2331868-4408 ;. - Intelligent systems reference library ;v.24..

Nature-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.

This 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.

ISBN: 9783031175442$q(electronic bk.)

Standard No.: 10.1007/978-3-031-17544-2doiSubjects--Topical Terms:

183292
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Nature-inspired optimization methodologies in biomedical and healthcare
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520 $a This 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.
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