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.