Springer - Nature-Inspired Methods for Smart Healthcare Systems

Nature-Inspired Methods for Smart Healthcare Systems and Medical Data by Springer provides a comprehensive collection of high-quality research focused on solving complex challenges in smart healthcare. This book serves as a vital resource for academics and engineers looking to develop new theories, frameworks, architectures, and algorithms designed for real industry use. The text explores recent theoretical and practical applications of metaheuristics and optimization within various smart healthcare contexts. Readers will learn how optimization techniques can be used to obtain optimal parameters in machine learning (ML) and deep learning (DL) technologies. By providing an open platform for sharing unique ideas, this work investigates the potential convergence of existing technologies to improve medical data management and smart healthcare applications. It is an essential addition to any library focused on the intersection of artificial intelligence and medical science.