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Artificial Intelligence Technology in Healthcare

- Security and Privacy Issues

About Artificial Intelligence Technology in Healthcare

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focusses on current issues with patients' privacy and data security including data breaches in healthcare organizations, unauthorized access to patients' information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing AI-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple technologies (i.e., IoT, Federated Computing, and AI) for managing and securing smart healthcare systems. Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing based real-time health monitoring. Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches. Focusses on latest research on privacy, security, and threat detection on COVID19 through IoT. Illustrates initiatives for research in smart computing for advanced healthcare management systems. This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.

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  • Language:
  • English
  • ISBN:
  • 9781032428390
  • Binding:
  • Hardback
  • Published:
  • September 4, 2024
  • Dimensions:
  • 152x229x19 mm.
  • Weight:
  • 608 g.
Delivery: 2-3 weeks
Expected delivery: January 12, 2025

Description of Artificial Intelligence Technology in Healthcare

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focusses on current issues with patients' privacy and data security including data breaches in healthcare organizations, unauthorized access to patients' information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing AI-based security mechanisms which can gather or share data across several healthcare applications securely and privately.
Features:

Combines multiple technologies (i.e., IoT, Federated Computing, and AI) for managing and securing smart healthcare systems.
Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing based real-time health monitoring.
Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches.
Focusses on latest research on privacy, security, and threat detection on COVID19 through IoT.
Illustrates initiatives for research in smart computing for advanced healthcare management systems. This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.

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