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Oncology Informatics: Using Health Information Technology to Improve Processes and Outcomes in Cancer Care encapsulates National Cancer Institute-collected evidence into a format that is optimally useful for hospital planners, physicians, researcher, and informaticians alike as they collectively strive to accelerate progress against cancer using informatics tools. This book is a formational guide for turning clinical systems into engines of discovery as well as a translational guide for moving evidence into practice. It meets recommendations from the National Academies of Science to "reorient the research portfolio" toward providing greater "cognitive support for physicians, patients, and their caregivers" to "improve patient outcomes." Data from systems studies have suggested that oncology and primary care systems are prone to errors of omission, which can lead to fatal consequences downstream. By infusing the best science across disciplines, this book creates new environments of "Smart and Connected Health." Oncology Informatics is also a policy guide in an era of extensive reform in healthcare settings, including new incentives for healthcare providers to demonstrate "meaningful use" of these technologies to improve system safety, engage patients, ensure continuity of care, enable population health, and protect privacy. Oncology Informatics acknowledges this extraordinary turn of events and offers practical guidance for meeting meaningful use requirements in the service of improved cancer care. Anyone who wishes to take full advantage of the health information revolution in oncology to accelerate successes against cancer will find the information in this book valuable. Presents a pragmatic perspective for practitioners and allied health care professionals on how to implement Health I.T. solutions in a way that will minimize disruption while optimizing practice goals Proposes evidence-based guidelines for designers on how to create system interfaces that are easy to use, efficacious, and timesaving Offers insight for researchers into the ways in which informatics tools in oncology can be utilized to shorten the distance between discovery and practice
This book constitutes the proceedings of the Third International Conference on Technologies and Innovation, CITI 2017, held in Guayaquil, Ecuador, in October 2017. The 24 papers presented in this volume were carefully reviewed and selected from 68 submissions. They were organized in topical sections named: cloud and mobile computing; knowledge based and expert systems; applications in healthcare and wellness; e-learning; and ICT in agronomy.
Photoplethysmography: Technology, Signal Analysis, and Applications is the first comprehensive volume on the theory, principles, and technology (sensors and electronics) of photoplethysmography (PPG). It provides a detailed description of the current state-of-the-art technologies/optical components enabling the extreme miniaturization of such sensors, as well as comprehensive coverage of PPG signal analysis techniques including machine learning and artificial intelligence. The book also outlines the huge range of PPG applications in healthcare, with a strong focus on the contribution of PPG in wearable sensors and PPG for cardiovascular assessment. - Presents the underlying principles and technology surrounding PPG - Includes applications for healthcare and wellbeing - Focuses on PPG in wearable sensors and devices - Presents advanced signal analysis techniques - Includes cutting-edge research, applications and future directions
This book gathers extended contributions to the workshop on Long-Term Digital Care, LTC-2021, organized by the Università Politecnica delle Marche (UNIVPM), Ancona, Italy, and the Hochschule Konstanz (HTWG), Germany, in November 2021, and funded by the DAAD Joint Mobility Program. It covers innovative, practice-oriented approaches that are expected to foster digital health care, with a special focus on improving internationalization and accessibility. The book, which bridges between technological and social disciplines, reports on selected studies with the main goals of: establishing a comparison of Long-Term Digital Care approaches, with focus on exchange and networking processes; defining practical roadmaps for digital social innovation; establishing concepts and methods for process evaluation and sustainability. It offers a timely snapshot on technologies for patient monitoring and assistant systems, medical data analysis and image processing, digital platforms and advanced diagnostics techniques, and discusses important concepts relating to traceable process evaluation, networking and accessibility. It aims at informing, yet it is also intended to inspire and foster a stronger collaboration across disciplines, countries, as well as academic and professional institutions.
Several internal and external factors have been identified to estimate and control the psycho-biological stress of training in order to optimize training responses and to avoid fatigue, overtraining and other undesirable health effects of an athlete. An increasing number of lightweight sensor-based wearable technologies (“wearables”) have entered the sports technology market. Non-invasive sensor-based wearable technologies could transmit physical, physiological and biological data to computing platform and may provide through human-machine interaction (smart watch, smartphone, tablet) bio-feedback of various parameters for training load management and health. However, in theory, several wearable technologies may assist to control training load but the assessment of accuracy, reliability, validity, usability and practical relevance of new upcoming technologies for the management of training load is paramount for optimal adaptation and health.
The Second International Conference on Innovations in Computing Research (ICR’23) brings together a diverse group of researchers from all over the world with the intent of fostering collaboration and dissemination of the innovations in computing technologies. The conference is aptly segmented into six tracks: Data Science, Computer and Network Security, Health Informatics and Medical Imaging, Computer Science and Computer Engineering Education, Internet of Things, and Smart Cities/Smart Energy. These tracks aim to promote a birds-of-the-same-feather congregation and maximize participation. The Data Science track covers a wide range of topics including complexity score for missing data, deep learning and fake news, cyberbullying and hate speech, surface area estimation, analysis of gambling data, car accidents predication model, augmenting character designers’ creativity, deep learning for road safety, effect of sleep disturbances on the quality of sleep, deep learning-based path-planning, vehicle data collection and analysis, predicting future stocks prices, and trading robot for foreign exchange. Computer and Network Security track is dedicated to various areas of cybersecurity. Among these are decentralized solution for secure management of IoT access rights, multi-factor authentication as a service (MFAaaS) for federated cloud environments, user attitude toward personal data privacy and data privacy economy, host IP obfuscation and performance analysis, and vehicle OBD-II port countermeasures. The Computer Science and Engineering Education track enfolds various educational areas, such as data management in industry–academia joint research: a perspective of conflicts and coordination in Japan, security culture and security education, training and awareness (SETA), influencing information security management, engaging undergraduate students in developing graphical user interfaces for NSF funded research project, and emotional intelligence of computer science teachers in higher education. On the Internet of Things (IoT) track, the focus is on industrial air quality sensor visual analytics, social spider optimization meta-heuristic for node localization optimization in wireless sensor networks, and privacy aware IoT-based fall detection with infrared sensors and deep learning. The Smart Cities and Smart Energy track spans various areas, which include, among others, research topics on heterogeneous transfer learning in structural health monitoring for high-rise structures and energy routing in energy Internet using the firefly algorithm.
The convergence of quantum technologies and biomedical intelligence is a frontier of boundless potential. The quantum advancements revolutionize disease detection, personalized medicine, and health monitoring frameworks while confronting the pressing challenge of accountability in machine learning systems within the biomedical domain. How do quantum innovations at the nexus of biomedical intelligence redefine biomedical research and healthcare, addressing critical inquiries such as the transformative potential of quantum computing, machine learning, and sensing technologies? Quantum Innovations at the Nexus of Biomedical Intelligence explores the intricate synergy between quantum mechanics and the biomedical domain. This book elucidates the profound implications and applications arising from the fusion of quantum computing, artificial intelligence, and biomedical sciences. This book introduces biomedical engineering, setting the stage for a deep dive into the transformative role of quantum computing and artificial intelligence. As the narrative unfolds, the text navigates the reader through the uncharted territories of quantum-enhanced machine learning, quantum sensing and their profound impact on diagnostics, personalized medicine, and health monitoring frameworks. The intersection of quantum computing and AI in medical advancements and cybersecurity is illuminated, offering a comprehensive understanding of the multifaceted applications of these cutting-edge technologies. This book is ideal for researchers, scientists, academics, and professionals across diverse disciplines in quantum innovations within biomedical intelligence.
Within the healthcare sector, a pressing need for transformative changes is growing. From chronic diseases to complex diagnostic procedures, the industry stands at the crossroads of technological innovation and a burgeoning demand for more efficient, precise interventions. Patient expectations are soaring, and the deluge of medical data is overwhelming traditional healthcare systems. It is within this challenging environment that AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications emerges as a beacon of insight and practical solutions. The traditional healthcare framework is struggling to keep pace with the diverse demands of patients and the ever-expanding volume of medical data. As diseases become more intricate, attempts to provide timely identification and precise treatment of ailments become increasingly elusive. The urgency for a paradigm shift in healthcare delivery is emphasized by the critical need for early interventions, particularly in disease prediction. This challenge necessitates a holistic approach that harnesses the power of artificial intelligence (AI) and innovative technologies to steer healthcare toward a more responsive and patient-centric future.