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Nature-Inspired Optimization Methodologies in Biomedical and Healthcare: Intelligent Systems Reference Library, cartea 233

Editat de Janmenjoy Nayak, Asit Kumar Das, Bighnaraj Naik, Saroj K. Meher, Sheryl Brahnam
en Limba Engleză Paperback – 15 noi 2023
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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Specificații

ISBN-13: 9783031175466
ISBN-10: 3031175468
Pagini: 293
Ilustrații: XVIII, 293 p. 111 illus., 77 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.44 kg
Ediția:1st ed. 2023
Editura: Springer International Publishing
Colecția Springer
Seria Intelligent Systems Reference Library

Locul publicării:Cham, Switzerland

Cuprins

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.

Textul de pe ultima copertă

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.


Caracteristici

Presents recent research on nature-inspired optimization methodologies in biomedical and health care Covers advanced methodologies, challenges, and solutions to diversified healthcare issues Presents applicable advanced mechanisms, automated tools, and possible approaches for solving biomedical problems