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.

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Yes, you can access Artificial Intelligence Technology in Healthcare by Neha Sharma,Durgesh Srivastava,Deepak Sinwar in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Biomedical Science. We have over one million books available in our catalogue for you to explore.

Information

Publisher

CRC Press

Year

2024

ISBN

9781040114919

Edition

Topic

Technology & Engineering

Subtopic

Biomedical Science

Index

Technology & Engineering

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