Nature-Inspired Optimization Methodologies in Biomedical and Healthcare (eBook, PDF)

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

• Format: PDF

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.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 293
• Erscheinungstermin: 14. November 2022
• Englisch
• ISBN-13: 9783031175442
• Artikelnr.: 66415936

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.