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Bio-Inspired Optimization for Medical Data Mining

Om Bio-Inspired Optimization for Medical Data Mining

Bio-Inspired Optimization for Medical Data is a groundbreaking book that delves into the convergence of nature's ingenious algorithms and cutting-edge healthcare technology. Through a comprehensive exploration of state-of-the-art algorithms and practical case studies, readers gain unparalleled insights into optimizing medical data processing, enabling more precise diagnosis, optimizing treatment plans, and ultimately advancing the field of healthcare. Organized into 15 chapters, readers learn about the theoretical foundation of pragmatic implementation strategies and actionable advice. In addition, it addresses current developments in molecular subtyping and how they can enhance clinical care. By bridging the gap between cutting-edge technology and critical healthcare challenges, this book is a pivotal contribution, providing a roadmap for leveraging nature-inspired algorithms. This is an indispensable resource that will drive significant changes in the healthcare sector.

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  • Språk:
  • Engelska
  • ISBN:
  • 9781394214181
  • Format:
  • Inbunden
  • Sidor:
  • 336
  • Utgiven:
  • 24. september 2024
  • Mått:
  • 159x237x27 mm.
  • Vikt:
  • 608 g.
  Fri leverans
Leveranstid: 2-4 veckor
Förväntad leverans: 13. oktober 2025

Beskrivning av Bio-Inspired Optimization for Medical Data Mining

Bio-Inspired Optimization for Medical Data is a groundbreaking book that delves into the convergence of nature's ingenious algorithms and cutting-edge healthcare technology. Through a comprehensive exploration of state-of-the-art algorithms and practical case studies, readers gain unparalleled insights into optimizing medical data processing, enabling more precise diagnosis, optimizing treatment plans, and ultimately advancing the field of healthcare. Organized into 15 chapters, readers learn about the theoretical foundation of pragmatic implementation strategies and actionable advice. In addition, it addresses current developments in molecular subtyping and how they can enhance clinical care. By bridging the gap between cutting-edge technology and critical healthcare challenges, this book is a pivotal contribution, providing a roadmap for leveraging nature-inspired algorithms. This is an indispensable resource that will drive significant changes in the healthcare sector.

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