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Full Description
Healthcare systems today are increasingly reliant on data gathered from multiple hospital systems, patient records or IoT devices. As more information is gathered, there is a need to ensure the data is kept and used securely. This edited book looks at secure big data analytics for healthcare and how the wealth of information is disseminated through open wireless channels to provide seamless coverage so that people can access and analyse the results obtained and intelligently manage and respond to a patient's needs.
The editors cover current and emerging frameworks, architectures, and solutions that address the requirements of secure big data analytics for the healthcare industry. The book also addresses the challenges of deploying security-based healthcare analytics for massive BDA (big data analytics) applications, through smart optimized network communication infrastructures, dense connectivity, and AI-driven models.
Topics include big data analytics, trustworthy data sharing, security challenges and privacy preserving techniques, authentication and access control schemes, deep learning models, risk modelling, and blockchain integration. The book provides a great reference for researchers in academia, network professionals, healthcare industry professionals, and researchers working towards emerging secure BDA solutions in 5G and beyond networks.
Contents
Chapter 1: Navigating the future: secure big data analytics in healthcare's 5G era
Chapter 2: Big data-driven medical image processing technologies and applications
Chapter 3: Challenges in big data analytics monitoring
Chapter 4: Security challenges in big data analytics
Chapter 5: Secure data sharing and collaboration in healthcare analytics
Chapter 6: Enhancing healthcare data security in the era of 5G and Big Data Analytics
Chapter 7: Privacy-preserving techniques for big data analytics in healthcare
Chapter 8: Enabling trustworthy data sharing and collaborative insights in healthcare analytics
Chapter 9: Communication aspects in 5G-assisted big data: a performance review against 4G-LTE frameworks
Chapter 10: Authentication and access control schemes in 5G-based healthcare systems
Chapter 11: Indexing-based approach in document-centric big data
Chapter 12: The AI-mental health dialogue: an investigation of their relationship
Chapter 13: Research on the application of Bayesian deep learning in medical big data
Chapter 14: Causal inference in healthcare: effective evaluation of clinical programs and other applications
Chapter 15: Clinical risk modeling using medical big data: a machine learning approach
Chapter 16: Unlock potential of artificial intelligence and blockchain integration for preserving privacy and medical data: high-fidelity data sharing and healthcare analytics lensing legal aspects
Chapter 17: The nuances of legal deviations in modern computing: a relook into the privacy and data protection laws in India and beyond
Chapter 18: Charting the course: secure big-data analytics and 5G in healthcare's transformative journey
