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The IEEE International Conference on Biomedical and Health Informatics (BHI) is a special topic conference of IEEE Engineering in Medicine and Biology Society (IEEE EMBS) BHI2017 is co located with the Annual HIMSS Conference Advancing health informatics has been identified as a grand challenge for engineering in the 21st century by the National Academy of Engineering Maintaining and improving human health will require integrative and novel informatics solutions to better translate discovery into clinics, re engineer care practices, and integrate big data of various health networks
The Wireless Power Transfer concept is continuously and rapidly evolving and new challenges arise every day. As a result of these rapid changes, the need for up-to-date texts that address this growing field from an interdisciplinary perspective persists. This book, organized into ten chapters, presents interesting novel solutions in the exploitation of the near- and far-field techniques of wireless power transfer that will be used in the near future, as well as a bird's eye view of some aspects related to an emerging technological area that will change our lives and will change the paradigm of how we use electrical equipment. The book covers the theory and also the practical aspects of technology implementation in a way that is suitable for undergraduate and graduate-level students, as well as researchers and professional engineers.
This book constitutes the refereed post-conference proceedings of the 10th International Conference on Mobile Communication and Healthcare, MobiHealth 2021, held in November 2021. Due to Covid-19 pandemic the conference was held virtually.
This two-volume set LNCS 13069-13070 constitutes selected papers presented at the First CAAI International Conference on Artificial Intelligence, held in Hangzhou, China, in June 2021. Due to the COVID-19 pandemic the conference was partially held online. The 105 papers were thoroughly reviewed and selected from 307 qualified submissions. The papers are organized in topical sections on applications of AI; computer vision; data mining; explainability, understandability, and verifiability of AI; machine learning; natural language processing; robotics; and other AI related topics.
This book collects research works of data-driven medical diagnosis done via Artificial Intelligence based solutions, such as Machine Learning, Deep Learning and Intelligent Optimization. Physical devices powered with Artificial Intelligence are gaining importance in diagnosis and healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.
This book gathers outstanding research papers presented at the International Conference on Information and Communication Technology for Development (ICICTD 2022), held on July 29–30, 2022, at the Institute of Information and Communication Technology (IICT), Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh. The topics covered are ICT in health care, ICT in e-commerce, e-governance, collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics and IoT, information systems, computer network, algorithms, and natural language processing.
This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.