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This book tackles the recent research trends on the role of AI in advancing automotive manufacturing, augmented reality, sustainable development in smart cities, telemedicine, and robotics. It sheds light on the recent AI innovations in classical machine learning, deep learning, Internet of Things (IoT), Blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP). The edited book covers empirical and reviews studies that primarily concentrate on the aforementioned issues, which would assist scholars in pursuing future research in the domain and identifying the possible future developments of AI applications.
The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data, information and knowledge in the healthcare domain. Features: Improves the quality of health data of a patient Presents a wide range of opportunities and renewed possibilities for healthcare systems Gives a way for carefully and meticulously tracking the provenance of medical records Accelerates the process of disease-oriented data and medical data arbitration Brings meaningful patient health outcomes Eradicates delayed clinical communications Helps the research intellectuals to step down further toward the disease and clinical data storage Creates more patient-centered services The precise focus of this handbook is on the potential applications and use of data informatics in healthcare, including clinical trials, tailored ailment data, patient and ailment record characterization and health records management.
This book aims at informing on new trends, challenges and solutions, in the multidisciplinary field of biomedical engineering. It covers traditional biomedical engineering topics, as well as innovative applications such as artificial intelligence in health care, tissue engineering , neurotechnology and wearable devices. Further topics include mobile health and electroporation-based technologies, as well as new treatments in medicine. Gathering the proceedings of the 8th European Medical and Biological Engineering Conference (EMBEC 2020), held on November 29 - December 3, 2020, in Portorož, Slovenia, this book bridges fundamental and clinically-oriented research, emphasizing the role of education, translational research and commercialization of new ideas in biomedical engineering. It aims at inspiring and fostering communication and collaboration between engineers, physicists, biologists, physicians and other professionals dealing with cutting-edge themes in and advanced technologies serving the broad field of biomedical engineering.
This book constitutes the proceedings of the 16th International Conference on Web Information Systems and Applications, WISA 2019, held in Qingdao, China, in September 2019. The 39 revised full papers and 33 short papers presented were carefully reviewed and selected from 154 submissions. The papers are grouped in topical sections on machine learning and data mining, cloud computing and big data, information retrieval, natural language processing, data privacy and security, knowledge graphs and social networks, blockchain, query processing, and recommendations.
Human Cancer Diagnosis and Detection Using Exascale Computing The book provides an in-depth exploration of how high-performance computing, particularly exascale computing, can be used to revolutionize cancer diagnosis and detection; it also serves as a bridge between the worlds of computational science and clinical oncology. Exascale computing has the potential to increase our ability in terms of computation to develop efficient methods for a better healthcare system. This technology promises to revolutionize cancer diagnosis and detection, ushering in an era of unprecedented precision, speed, and efficiency. The fusion of exascale computing with the field of oncology has the potential to redefine the boundaries of what is possible in the fight against cancer. The book is a comprehensive exploration of this transformative unification of science, medicine, and technology. It delves deeply into the realm of exascale computing and its profound implications for cancer research and patient care. The 18 chapters are authored by experts from diverse fields who have dedicated their careers to pushing the boundaries of what is achievable in the realm of cancer diagnosis and detection. The chapters cover a wide range of topics, from the fundamentals of exascale computing and its application to cancer genomics to the development of advanced imaging techniques and machine learning algorithms. Explored is the integration of data analytics, artificial intelligence, and high-performance computing to move cancer research to the next phase and support the creation of novel medical tools and technology for the detection and diagnosis of cancer. Audience This book has a wide audience from both computer sciences (information technology, computer vision, artificial intelligence, software engineering, applied mathematics) and the medical field (biomedical engineering, bioinformatics, oncology). Researchers, practitioners and students will find this groundbreaking book novel and very useful.
Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023), July 20–24, 2023, San Francisco, USA
IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization. The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand. - Provides state-of-art methods and current trends in data analytics for the healthcare industry - Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques - Discusses several potential AI techniques developed using IoT for the healthcare industry - Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages
This book gathers the proceedings of the eighth Future of Information and Computing Conference, which was held successfully in virtual mode. It received a total of 369 paper submissions from renowned and budding scholars, academics, and distinguished members of the industry. The topics fanned across various fields involving computing, Internet of Things, data science, and artificial intelligence. Learned scholars from all walks of life assembled under one roof to share their unique, original, and breakthrough researches and paved a new technological path for the world. Many of the studies seek to change the face of the world itself. Their innovative thinking indeed aims to solve several gruesome problems in the field of communication, data science, ambient intelligence, networking, computing, security, and privacy. The authors have strived to render valuable pieces of study in this edition and hope to acquire enthusiastic support from the readers.