Securing Next-Generation Connected Healthcare Systems
Artificial Intelligence Technologies
- 1st Edition - May 14, 2024
- Latest edition
- Editors: Deepak Gupta, Aboul Ella Hassanien
- Language: English
Securing Next-Generation Connected Healthcare Systems: Artificial Intelligence Technologies focuses on the crucial aspects of IoT security in a connected environment, which will n… Read more
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Description
Description
Researchers, data scientists, students, and professionals interested in the application of artificial intelligence in healthcare management, data security of connected healthcare systems and related fields, specifically on data intensive secured systems and computing environments, will finds this to be a welcomed resource.
Key features
Key features
- Covers the latest next generation connected healthcare technologies using parallel computing
- Presents all the security aspects in next-generation technologies for healthcare
- Utilizes technologies such as blockchain and its integration with IoT for communication, data security, and trust management
- Discusses privacy and security issues and challenges in data intensive cloud computing environment
- Dives into the concept of parallel and distributed computing technologies and their applications in the real world
Readership
Readership
Table of contents
Table of contents
2. Ai-Driven IoT for Smart Health Care: Security and Privacy Issues
3. Securing Healthcare Systems Using Future AI Technology: A State-Of-The-Art Systematic Literature Review and Future Research Directions
4. New AI Technology Protects Privacy in Healthcare Settings
5. Risk Monitoring Strategy for Confidentiality of Healthcare Information
6. Securing Healthcare AI with Confidential Computing
7. A Management Method of Chronic Diseases in the Elderly Based on IoT Security Environment
8. Secure and Pervasive Communication Framework Using Named Data Networking for Connected Healthcare
9. A Novel Hybrid Encryption Method to Secure Healthcare Data in IoT-Enabled Healthcare Infrastructure
10. Securing E-Health Application of Cloud Computing Using Hyperchaotic Image Encryption Framework
11. Parkinson and Essential Tremor Classification to Identify the Patient’s Risk Based on Tremor Severity
12. A Novel Method for Lung Nodule Detection in Computed Tomography Scans Based on Boolean Equations and Vector of Filters Techniques
13. Stacking Approach for Accurate Invasive Ductal Carcinoma Classification
14. A New Blockchain and Fog Computing Model for Blood Pressure Medical Sensor Data Storage
15. A Secure Energy-Efficient Routing Protocol for Disease Data Transmission Using IOMT
16. An Efficient Framework for Semantically-Correlated Term Detection and Sanitization In Clinical Documents
17. Remote Monitoring System Using Light Fidelity and Infrared Technologies
18. A Tree Classifier Based Network Intrusion Detection Model for Internet of Medical Things
19. AI-driven Cybersecurity for Healthcare Cyber Physical Systems
20. Blockchain Security Connecting Different IoT Healthcare Protocols
Product details
Product details
- Edition: 1
- Latest edition
- Published: May 20, 2024
- Language: English
About the editors
About the editors
DG
Deepak Gupta
Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision.
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