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Springer Nature-Inspired Optimization in Biomedical Healthcare - Springer Vol 233

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Description

This volume explores nature-inspired optimization methodologies applied to biomedical and healthcare challenges, part of Springer's Intelligent Systems Reference Library series. The book examines how algorithms derived from natural processes-such as evolutionary computation, swarm intelligence, and other bio-inspired techniques-solve complex problems in medical imaging, drug discovery, patient diagnosis, treatment planning, and healthcare systems optimisation. Researchers, practitioners, and students in biomedical engineering, computer science, and healthcare informatics will find comprehensive coverage of theoretical foundations and practical applications. The work bridges computational intelligence and modern medicine, offering insights into how nature-inspired approaches improve diagnostic accuracy, accelerate research, and enhance clinical decision-making across diverse healthcare domains.

Key Features

Springer's Intelligent Systems Reference Library Volume 233 provides peer-reviewed research on nature-inspired algorithms in biomedical applications.

Covers evolutionary computation, swarm intelligence, and genetic algorithms adapted for healthcare problem-solving and optimisation.

Addresses real-world biomedical challenges including medical imaging analysis, drug discovery acceleration, and patient diagnosis support.

Combines theoretical frameworks with practical case studies demonstrating nature-inspired methodology effectiveness in healthcare settings.

Suitable for researchers, engineers, and healthcare professionals seeking advanced computational approaches to complex medical problems.

Part of a comprehensive series on intelligent systems, ensuring rigorous academic standards and cutting-edge methodology coverage.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
15 November 2023
Listed Since
20 October 2023

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