Multimedia and Multimodal Intelligence for Secure and Sustainable Healthcare: Theoretical and Practical Insights

Providing a comprehensive examination of artificial intelligence techniques that integrate heterogeneous healthcare data to support intelligent, secure, and sustainable healthcare systems, this book presents both theoretical foundations and practical methodologies for multimodal data fusion, representation learning, decision-making using medical images, biosignals, electronic health records, wearable sensors, text, and multimedia data.

• 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.

Multimedia and Multimodal Intelligence for Secure and Sustainable Healthcare 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.

Sita Rani works in the Department of Computer Science and Engineering at Guru Nanak Dev Engineering College, Ludhiana. She has more than 20 years of academic, administration, and research experience. Her research interest includes Data Science, Artificial Intelligence, Machine Learning, Blockchain Technology, Smart Healthcare, and Sustainable Development.

Sui Yang Khoo is an Associate Professor in Electrical & Electronics Engineering, Deakin University, Victoria, Australia. Sui Yang's research interests include stochastic differential equations, variable structure control, co-operative control, robotics, adaptive signal processing, time-varying systems, and machine learning.

Ashima Kalra is currently serving as an Associate Professor in the Department of Electronics and Communication Engineering at Chandigarh Engineering College (CGC), Landran. Her contributions have been widely recognized through multiple academic excellence awards, including the prestigious Women Leadership Award, reflecting her sustained commitment to quality education, impactful research, and leadership in engineering education.

Hemant Kumar Saini works as an academic at the School of Computer Science Engineering at Bennett University (The Times Group), Greater Noida, India and Lincoln University, Malaysia. He has more than 14 years of teaching experience. His research includes digital transformation technologies such as Artificial Intelligence (AI), Quantum Computing, Internet of Things (IoT), Blockchain, Edge and Serverless computing, Cloud-native computing, and Digital Twins.