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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This book 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 develop AI-based security mechanisms which can gather or share data across healthcare applications.
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1. Artificial Intelligence in Healthcare: A Paradigm Shift. 2. AI’s Implication in Healthcare and Medical Systems. 3. Advancements of Artificial Intelligence in Healthcare. 4. A Review of Deep Learning Applications in Modernized Healthcare Services. 5. An Empirical Evaluation of Learning Models for the classification of Fall Detection dataset. 6. Review in Healthcare using Augmented Reality/Virtual Reality: An IoT perspective. 7. Shooting method for solving two-point boundary value problems in ODEs numerically and applications to medical science. 8. Key Management in Healthcare using IoMT. 9. Security issues related to COVID data using Artificial Intelligence (AI). 10. Security Issues and Defense Mechanism Using IoMT. 11. Threat Modeling in Healthcare Systems. 12. Use of Block Chain Technology for Privacy and Threat Detection. 13. Blockchain based Decentralized Biometric Authentication System for Vulnerability Analysis. 14. Security Issues Related to Cervical Cancer Research: A Bibliometric Analysis.
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Produktdetaljer

ISBN
9781032428390
Publisert
2024-09-05
Utgiver
Vendor
CRC Press
Vekt
766 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
U, P, 05, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
312

Biographical note

Neha Sharma is working as Assistant Professor in Department of Computer Science and Engineering in Chitkara University Institute of Engineering & Technology, Chitkara University, Rajpura, Punjab, India. She has received the M.Tech.(CSE), Ph.D. (Computer Science) degree in the area of Computer Science with vast teaching experience of more than 12 Years in reputed organisation. She has more than 25 international publications in the reputed peer reviewed journals including IEEE xplore, SCOPUS and SCI indexed. Her main area of research is the Image processing, Machine learning, Deep Learning, Cyber Security. She has also published several National & International Patents under the Intellectual Property Rights of Government of India & Abroad. She is actively associated in NAAC preparations at Universities interface. She is associated in many highly impact society membership like IEEE (Senior Member), ACM, ISTE (Life-time Member).

Durgesh Srivastava is an Associate Professor at the Department of Computer Science and Engineering in Chitkara University Institute of Engineering & Technology, Chitkara University, Rajpura, Punjab, India. He received his PhD degree in Computer Science & Engineering from IKG Punjab Technical University, Jalandhar, Punjab, India in 2020. He received B. Tech. degree in Information & Technology (IT) from MIET, Meerut, UP in 2006 and ME in Software Engineering from Birla Institute of Technology (BIT), Mesra, Ranchi, Jharkhand, India in 2008. He has Fourteen years of teaching experience. His research interests include Machine Learning, Soft Computing, Pattern Recognition, Software engineering, Modeling, and design, etc. He has authored several research papers/book in reputed international/national journals and conference/seminar.

Deepak Sinwar is an Assistant Professor at the Department of Computer and Communication Engineering, School of Computing & Information Technology at Manipal University Jaipur, Jaipur, Rajasthan, India. He received his Ph.D and M.Tech degrees in Computer Science and Engineering in 2016 and 2010 respectively; and B.Tech (with honors) in Information Technology in 2008. His research interests include Computational Intelligence, Data Mining, Machine Learning, Reliability Theory, Computer Networks, and Pattern Recognition. He is an enthusiastic and motivating technocrat with more than 11 years of research and academic experience. He is a life member of the Indian Society for Technical Education (India), and a member of ACM and IEEE professional society.