Nature-Inspired Optimization Methodologies in Biomedical and Healthcare

Herausgegeben:Nayak, Janmenjoy; Das, Asit Kumar; Naik, Bighnaraj; Meher, Saroj K.; Brahnam, Sheryl

• Gebundenes Buch

Produktbeschreibung

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.

Produktdetails

• Intelligent Systems Reference Library 233
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-17543-5
• 1st ed. 2023
• Seitenzahl: 312
• Erscheinungstermin: 15. November 2022
• Englisch
• Abmessung: 241mm x 160mm x 23mm
• Gewicht: 635g
• ISBN-13: 9783031175435
• ISBN-10: 3031175433
• Artikelnr.: 65379497

Inhaltsangabe

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.