Metaheuristics Algorithms for Medical Applications 1st Edition

Capture the future of healthcare optimization with Metaheuristics Algorithms for Medical Applications, 1st Edition by Mohamed Abdel‑Basset, Reda Mohamed, and Mohamed Elhoseny. This authoritative guide unlocks advanced, nature‑inspired techniques designed to solve complex medical problems—from diagnostic classification and image segmentation to treatment planning and resource scheduling.

Discover clear explanations of popular and cutting‑edge metaheuristic algorithms (genetic algorithms, particle swarm optimization, ant colony optimization, differential evolution, and more) and how they’re tailored to real-world medical challenges. Rich case studies and comparative analyses illustrate practical performance metrics, helping researchers and practitioners choose and fine‑tune the right approach for their needs.

Ideal for graduate students, data scientists, biomedical engineers, clinicians, and hospital IT teams, this volume bridges theory and practice—translating mathematical models into actionable strategies for improved patient outcomes, workflow efficiency, and decision support. Emphasizing reproducible evaluation and robust design, it supports deployment across hospitals, research centers, and global healthcare systems.

Whether you’re advancing academic research, building diagnostic tools, or optimizing clinical operations, this book equips you with the tools to innovate responsibly in healthcare. Stay at the forefront of computational medicine—add Metaheuristics Algorithms for Medical Applications, 1st Edition to your professional library and transform complex medical data into smarter, faster solutions for patients worldwide.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.