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Full Description
This book provides a comprehensive examination of artificial intelligence techniques that integrate heterogeneous healthcare data to support intelligent, secure, and sustainable healthcare systems. It presents both theoretical foundations and practical methodologies for multimodal data fusion, representation learning, and decision-making using medical images, bio signals, electronic health records, wearable sensors, text, and multimedia data.
Features:
Illustrates analyzing and integrating multiple modalities of healthcare data, such as medical images, electronic health records, bio signals, and genomic data.
Emphasizes the role of multimedia intelligence in healthcare by leveraging advanced artificial intelligence techniques to analyze diverse data formats, including text, images, audio, and video.
Presents practical applications that ensure secure healthcare data management and sustainable solutions, focusing on improving patient care and enhancing diagnostics.
Covers the different security mechanisms applied in multimodal and multimedia-based healthcare applications.
Showcases the role of advanced artificial intelligence and machine learning methods, including privacy-preserving technologies, blockchain, and explainable artificial intelligence tailored for secure healthcare.
The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering.
Contents
Chapter 1. Introduction to multimodal and multimedia intelligence for healthcare. Chapter 2. Technological Innovation in AI for Healthcare Applications. Chapter 3. Data Fusion Techniques for Multimodal Integration. Chapter 4. Cloud-Based Solutions for Sustainable Biomedical Data Processing and Management. Chapter 5. Integrating Framework in Mobile Cloud Computing and Multimodal Data for Pervasive Healthcare Systems. Chapter 6. A Multimodal & Multilingual approach to sentiment analysis for emotion recognition. Chapter 7. Multimodal Machine Learning Approaches for Heart Disease Detection and Control. Chapter 8. Multimodal Intelligence for Cancer Management: A New Dimension in Healthcare Applications. Chapter 9. Generative Multimodal Framework for Adaptive Therapeutic Game Content in Digital Health Applications. Chapter 10. Healthcare and Assistive Technologies: Multimodal AI for Rehabilitation, Monitoring and Patient Independence. Chapter 11. AI-Powered Smart Hospitals and Digital Twin Healthcare Systems. Chapter 12. Securing the Healthcare with Blockchain Powered Multimedia Medicare System. Chapter 13. Blockchain and AI for Sustainable Healthcare. Chapter 14. Decentralized Incentives: Tokenomics and Micropayments in Modern Healthcare. Chapter 15. Open Research Challenges and Futuristic Directions for Multimodal Healthcare Security
