Using Multimedia Systems Tools And Technologies For Smart Healthcare Services

With the advancement of sensorial media, objects, and technologies, multimedia can play a significant role in smart healthcare by offering better insight of heterogeneous healthcare multimedia content to support affordable and quality patient care. While researchers and the scientific community have been making advances in the study of multimedia tools and healthcare services individually, very little attention has been given to developing cost effective and affordable smart healthcare services. Multimedia-based smart healthcare has the potential to revolutionize many aspects of our society; however, many technical challenges must be addressed before this potential can be realized. Using Multimedia Systems, Tools, and Technologies for Smart Healthcare Services includes high-quality research on the recent advances in various aspects of intelligent interactive multimedia technologies in healthcare services and, more specifically, in the state-of-the-art approaches, methodologies, and systems in the design, development, deployment, and innovative use of multimedia systems, tools, and technologies for providing insights into smart healthcare service demands. Covering topics such as genetic algorithms, automatic classification of diseases, and structural equation modeling, this premier reference source is an essential resource for hospital administrators, medical professionals, health IT specialists, hospital technicians, students and faculty of higher education, researchers, and academicians.

This book includes high-quality research on various aspects of intelligent interactive multimedia technologies in healthcare services. The topics covered in the book focus on state-of-the-art approaches, methodologies, and systems in the design, development, deployment, and innovative use of multimedia systems, tools, and technologies in healthcare. The volume provides insights into smart healthcare service demands. It presents all information about multimedia uses in e-healthcare applications. The book also includes case studies and self-assessment problems for readers and future researchers. This book proves to be a valuable resource to know how AI can be an alternative tool for automated and intelligent analytics for e-healthcare applications.

This new volume explores how the merging of interactive multimedia with artificial intelligence has created new and advanced tools in healthcare. It looks at how the latest technologies (artificial intelligence, deep learning, machine learning, big data, IoT, smart device, etc.) help to manage health data, diagnose health issues, monitor treatment, predict pandemic diseases, and more. The book covers several important applications of multimedia in healthcare, including for data visualization purposes, for computer vision for elder healthcare monitoring, for detection of lung nodules, for management systems using machine learning techniques, and for fusion applications in medical image processing. The chapter authors discuss using data mining and machine learning techniques for COVID-19 diagnosis and prediction, in detecting knee osteoarthritis using texture descriptor algorithms, in applying algorithms in fetal ECG enhancement using blockchain for wearable internet of things in healthcare, and more. A chapter also reviews how doctors can make good use of genomics and genetic data through advanced technology. The book concludes with discussions of open issues, challenges, and future research directions for using intelligent interactive multimedia in healthcare. Key features: Provides an in-depth understanding of emerging technologies and integration of artificial intelligence, deep learning, big data, IoT in healthcare Details specific applications for the use of AI, big data, and IoT in healthcare Discusses how AI technology can help in formulating protective measures for COVID-19 and other diseases Includes case studies Intelligent Interactive Multimedia Systems for e-Healthcare Applications will be valuable to undergraduate and graduate students planning their careers in either industry or research and to software engineers for using multimedia with artificial intelligence, deep learning, big data, and IoT for healthcare applications.

PRIVACY PRESERVATION of GENOMIC and MEDICAL DATA Discusses topics concerning the privacy preservation of genomic data in the digital era, including data security, data standards, and privacy laws so that researchers in biomedical informatics, computer privacy and ELSI can assess the latest advances in privacy-preserving techniques for the protection of human genomic data. Privacy Preservation of Genomic and Medical Data focuses on genomic data sources, analytical tools, and the importance of privacy preservation. Topics discussed include tensor flow and Bio-Weka, privacy laws, HIPAA, and other emerging technologies like Internet of Things, IoT-based cloud environments, cloud computing, edge computing, and blockchain technology for smart applications. The book starts with an introduction to genomes, genomics, genetics, transcriptomes, proteomes, and other basic concepts of modern molecular biology. DNA sequencing methodology, DNA-binding proteins, and other related terms concerning genomes and genetics, and the privacy issues are discussed in detail. The book also focuses on genomic data sources, analyzing tools, and the importance of privacy preservation. It concludes with future predictions for genomic and genomic privacy, emerging technologies, and applications. Audience Researchers in information technology, data mining, health informatics and health technologies, clinical informatics, bioinformatics, security and privacy in healthcare, as well as health policy developers in public and private health departments and public health.

Academic scholars and professionals are currently grappling with hurdles in optimizing diagnostic processes, as traditional methodologies prove insufficient in managing the intricate and voluminous nature of medical data. The diverse range of imaging techniques, spanning from endoscopy to magnetic resonance imaging, necessitates a more unified and efficient approach. This complexity has created a pressing need for streamlined methodologies and innovative solutions. Academic scholars find themselves at the forefront of addressing these challenges, seeking ways to leverage AI's full potential in improving the accuracy of medical imaging diagnostics and, consequently, enhancing overall patient outcomes. Future of AI in Medical Imaging, stands as a solution to the challenges faced by academic scholars in the realm of medical imaging. The book lays a solid groundwork for understanding the complexities of medical imaging systems. Through an exploration of various imaging modalities, it not only addresses the current issues but also serves as a guide for scholars to navigate the landscape of AI-integrated medical diagnostics. This collaborative effort not only illuminates the existing hurdles of medical imaging but also looks towards a future where AI-driven diagnostics and personalized medicine become indispensable tools, significantly elevating patient outcomes.

This book presents a particular area of interest in computing psychiatry with the modelling of mood and anxiety disorders. It highlights various methods for building these models. Clinical applications are prevalent due to the growth and interaction of these multiple approaches. Besides, it outlines some original predictive and computational modelling ideas for enhancing psychological treatment interventions. Computational psychiatry combines multiple levels and types of computation with different data types to improve mental illness understanding, prediction, and treatment.

Today, computation is an essential component of every technology. However, there has not been much research on quantum computing, even though it has the capability to solve complex problems in an efficient way. Further study is required to fully understand the uses and benefits of this technology. The Handbook of Research on Quantum Computing for Smart Environments presents investigating physical realizations of quantum computers, encoders, and decoders, including photonic quantum realization, cavity quantum electrodynamics, and many more topics on Bits to Qubits. Covering key topics such as machine learning, software, quantum algorithms, and neural networks, this major reference work is ideal for engineers, computer scientists, physicists, mathematicians, researchers, academicians, scholars, practitioners, instructors, and students.

The security of assistive systems in AI-based digital health communication is a critical challenge, leaving users vulnerable to threats and attacks. AI-Based Digital Health Communication for Securing Assistive Systems provides a comprehensive solution by integrating artificial intelligence (AI) with cybersecurity measures. Edited by Vijeyananthan Thayananthan, this groundbreaking book equips assistive technology developers, researchers, and professionals with the knowledge and tools necessary to safeguard these systems and protect user privacy and well-being. Covering topics such as assistive communication technology, secure assistive technologies, robotics, and AI-based eHealth applications, the book explores innovative approaches to enhance the security of assistive systems. It offers practical guidance and insights into the strategic role of AI-based cybersecurity, empowering readers to protect individuals relying on assistive systems. Professionals, researchers, and scholars in the field of digital health communication will find this book invaluable, especially assistive technology developers looking to enhance their understanding of AI-based cybersecurity. Postgraduate students, research scientists, and academic research scholars will also benefit from the book's valuable insights and advancements. Executives and healthcare management professionals involved in digital health communication can leverage the book's expertise to drive organizational development and create a safer environment for individuals dependent on assistive systems.