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Artificial Intelligence Technology in Healthcare: Security and Privacy Issues (Advances in Smart Healthcare Technologies)

✍ Scribed by Neha Sharma (editor), Durgesh Srivastava (editor), Deepak Sinwar (editor)


Publisher
CRC Press
Year
2024
Tongue
English
Leaves
312
Edition
1
Category
Library

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✦ Synopsis


Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses 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 artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately.

Features:

    • Combines multiple technologies (i.e., Internet of Things [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.

    • Focuses on latest research on privacy, security, and threat detection on COVID-19 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.

    ✦ Table of Contents


    Cover
    Half Title
    Series Page
    Title Page
    Copyright Page
    Table of Contents
    Preface
    About the Editors
    Chapter 1 Artificial Intelligence in Healthcare: A Paradigm Shift
    Chapter 2 AI’s Implications in Healthcare and Medical Systems
    Chapter 3 Advancements of Artificial Intelligence in Healthcare
    Chapter 4 A Review of Deep Learning Applications in Modernized Healthcare Services
    Chapter 5 An Empirical Evaluation of Learning Models for the Classification of Fall Detection Dataset
    Chapter 6 Review in Healthcare Using Augmented Reality/Virtual Reality: An IoT Perspective
    Chapter 7 Shooting Method for Solving Two-point Boundary Value Problems in ODEs Numerically and Applications to Medical Science
    Chapter 8 Key Management in Healthcare Using IoMT
    Chapter 9 Security Issues Related to COVID Data Using Artificial Intelligence (AI)
    Chapter 10 Security Issues and Defense Mechanism Using IoMT
    Chapter 11 Threat Modeling in Health Care Systems
    Chapter 12 Use of Blockchain Technology for Privacy and Threat Detection
    Chapter 13 Blockchain-Based Decentralized Biometric Authentication System for Vulnerability Analysis
    Chapter 14 Security Issues Related to Cervical Cancer Research: A Bibliometric Analysis
    Index


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