Artificial Intelligence for Medical Data Processing
eBook - ePub

Artificial Intelligence for Medical Data Processing

Algorithms and Applications

  1. 340 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence for Medical Data Processing

Algorithms and Applications

About this book

This book showcases the potential of artificial intelligence to transform diagnostics, predictive analytics, personalized treatment, and healthcare resource optimization. It presents real-world applications and emerging trends, such as quantum computing, federated learning, and edge artificial intelligence.

Features:

  • Explores the intersection of artificial intelligence and neuroscience, including applications in understanding brain disorders, cognitive functions, and neuroimaging data processing.
  • Provides insights into emerging technologies such as quantum computing and their potential to revolutionize medical data processing, accelerate artificial intelligence algorithms, and solve previously intractable problems in healthcare.
  • Analyzes advanced strategies for identifying and mitigating biases in artificial intelligence models, ensuring compliance with global healthcare regulations and fostering ethical artificial intelligence adoption.
  • Discusses the application of multi-agent artificial intelligence systems in optimizing hospital operations, emergency response, and resource management in healthcare ecosystems.
  • Covers the use of generative models, such as generative adversarial network and variational autoencoders, in drug design, protein structure prediction, and the creation of synthetic biomedical datasets.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, biomedical engineering, drug delivery, and information technology.

Information

Publisher
CRC Press
Year
2026
Print ISBN
9781041153863
Edition
1
eBook ISBN
9781040961667

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Contents
  7. Preface
  8. About the Editors
  9. List of Contributors
  10. 1 A comparative overview of artificial intelligence for medical data processing
  11. 2 AI-powered medical data processing: From algorithms to intelligent healthcare systems
  12. 3 Natural language processing in healthcare: Transforming clinical texts with context-aware systems
  13. 4 Advances in AI-driven medical imaging and diagnostics: A comprehensive review
  14. 5 AI-driven biomedical image processing for breast cancer diagnosis: Techniques, applications, and clinical integration
  15. 6 Hybrid deep learning and explainable AI for histopathological analysis and cancer biomarker detection
  16. 7 AI in multi-omics data integration for precision medicine
  17. 8 Artificial intelligence for EEG biomarker discovery in emotional disorders
  18. 9 Reinforcement learning in medicine: Foundational models for personalised decision support
  19. 10 Edge AI for real-time data fusion in wearables and IoT-based healthcare systems
  20. 11 AI-driven predictive analytics for disease forecasting, management, and prevention
  21. 12 Generative AI in drug discovery and biomedical applications
  22. 13 Explainable AI (XAI) in healthcare decision-making
  23. 14 Artificial intelligence applications in rural and remote healthcare delivery
  24. 15 Ethical AI in healthcare: Addressing bias, fairness, and regulatory compliance
  25. 16 Future horizons: Quantum computing and AI for medical innovations
  26. 17 Concluding perspectives: Consolidated insights, open challenges, and recommendations
  27. Index

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Yes, you can access Artificial Intelligence for Medical Data Processing by Chetna Sharma,Amandeep Kaur,Harpreet Singh in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Biomedical Science. We have over 1.5 million books available in our catalogue for you to explore.