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Modern medicine and healthcare are highly dependent on engineering, employing instrumentation and computer systems to aid investigation, diagnosis, treatment and patient management. The significant developments in the field of computational intelligence, combined with the emergence of high-performance computing is impacting society in many ways, and the health sector is no exception. The interface of high-performance computing, computational intelligence and medical science, has seen the emergence of intelligent medical systems. These systems can provide a deeper insight into many healthcare and medical problems. They can also aid in controlling, analyzing and the management of medical applications and can provide significant improvement in the quality of life and efficacy of clinical treatment. However, the successful application of high-performance computing in medicine requires in-depth knowledge and understanding of medical systems. This book focuses on the advances and applications of high-performance computing for medical systems and provides an insight into the latest developments in the field. It will help readers to understand the high-performance computing research domain as related to intelligent medical systems, its effect on our lives and its present limitations. Part of IOP Series in Next Generation Computing.
This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.
The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems’ design practices and computational intelligence tactics for medical usage. The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.
This book constitutes selected revised and extended papers from the 11th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2021, Barnaul, Russia, in May 2021. The 32 full papers presented in this volume were thoroughly reviewed and selected form 98 submissions. The papers are organized in topical sections on Hardware for High-Performance Computing and Signal Processing; Information Technologies and Computer Simulation of Physical Phenomena; Computing Technologies in Discrete Mathematics and Decision Making; Information and Computing Technologies in Automation and Control Science; and Computing Technologies in Information Security Applications.
A guide to intelligent decision and pervasive computing paradigms for healthcare analytics systems with a focus on the use of bio-sensors Intelligent Pervasive Computing Systems for Smarter Healthcare describes the innovations in healthcare made possible by computing through bio-sensors. The pervasive computing paradigm offers tremendous advantages in diversified areas of healthcare research and technology. The authors—noted experts in the field—provide the state-of-the-art intelligence paradigm that enables optimization of medical assessment for a healthy, authentic, safer, and more productive environment. Today’s computers are integrated through bio-sensors and generate a huge amount of information that can enhance our ability to process enormous bio-informatics data that can be transformed into meaningful medical knowledge and help with diagnosis, monitoring and tracking health issues, clinical decision making, early detection of infectious disease prevention, and rapid analysis of health hazards. The text examines a wealth of topics such as the design and development of pervasive healthcare technologies, data modeling and information management, wearable biosensors and their systems, and more. This important resource: Explores the recent trends and developments in computing through bio-sensors and its technological applications Contains a review of biosensors and sensor systems and networks for mobile health monitoring Offers an opportunity for readers to examine the concepts and future outlook of intelligence on healthcare systems incorporating biosensor applications Includes information on privacy and security issues on wireless body area network for remote healthcare monitoring Written for scientists and application developers and professionals in related fields, Intelligent Pervasive Computing Systems for Smarter Healthcare is a guide to the most recent developments in intelligent computer systems that are applicable to the healthcare industry.
The book Intelligent Healthcare: Infrastructure, Algorithms, and Management® cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning. This book will provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors. Main Features: Ø Immersive technologies in healthcare Ø Internet of medical things Ø Federated learning algorithms Ø Explainable AI in Pervasive Healthcare Ø New management principles using biomedical data Ø Secured healthcare management systems This book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue.
With emerging trends such as the Internet of Things, sensors and actuators are now deployed and connected everywhere to gather information and solve problems, and such systems are expected to be trustworthy, dependable and reliable under all circumstances. But developing intelligent environments which have a degree of common sense is proving to be exceedingly complicated, and we are probably still more than a decade away from sophisticated networked systems which exhibit human-like thought and intelligent behavior. This book presents the proceedings of four workshops and symposia: the 4th International Workshop on Smart Offices and Other Workplaces (SOOW’15); the 4th International Workshop on the Reliability of Intelligent Environments (WoRIE’15); the Symposium on Future Intelligent Educational Environments and Learning 2015 (SOFIEEe’15); and the 1st immersive Learning Research Network Conference (iLRN’15). These formed part of the 11th International Conference on Intelligent Environments, held in Prague, Czech Republic, in July 2015, which focused on the development of advanced, reliable intelligent environments, as well as newly emerging and rapidly evolving topics. This overview of and insight into the latest developments of active researchers in the field will be of interest to all those who follow developments in the world of intelligent environments.
This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
In 1991 the Federal Government initiated the multiagency High Performance Computing and Communications program (HPCC) to further the development of U.S. supercomputer technology and high-speed computer network technology. This overview by the Congressional Budget Office (CBO) concentrates on obstacles that might prevent the growth of the high-performance computing and data communications industries. The market for supercomputers, relative to that of other technologies, is small. The main obstacle to the rise of large commercial markets for HPCC-developed technology is that cheaper workstations may preempt further growth of the supercomputer market as a whole. In addition, an economic inertia may occur, as conventional supercomputers, working well, become difficult to dislodge in the marketplace. The National Research and Educational Network (NREN) is central to the HPCC program. The ways in which Internet is becoming the core of a national data network promise well for HPCC in the future, but HPCC technology might be precluded from having a substantial effect on the current markets if demand for high-speed communications does not emerge as envisaged by HPCC leaders. Cost considerations and policy directions for HPCC are discussed. Five tables, six figures, and one box illustrate the discussion. Three appendixes discuss HPCC technology spinoffs and speed calculations. (SLD)