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Multidisciplinarity and Interdisciplinarity in Health
The contributed volume "Multidisciplinarity and Interdisciplinarity in Health" is a health-centered volume of the Integrated Science Book series. Lack of confidence, lack of expertise, complexities of healthcare, the confusing nature of healthcare environments, and lack of organization and standardization can become obstacles to successful communication. This volume establishes how extensive is the interface between formal sciences and medical sciences on health-related issues. The book provides an overview of the value of the integration of formal, biological, and medical sciences and related products, i.e., health informatics and biomedical engineering, to frame a holistic approach to heal...
Digital Health in Focus of Predictive, Preventive and Personalised Medicine
The edition will cover proceedings of the second International conference on digital health Technologies (ICDHT 2019). The conference will address the topic of P4 medicine from the information technology point of view, and will be focused on the following topics: - Artificial Intelligence for health • Knowledge extraction • Decision-aid systems • Data analysis and risk prediction • Machine learning, deep learning - Health data processing • Data preprocessing, cleaning, management and mining • Computer-aided detection • Big data analysis, prediction and prevention • Cognitive algorithms for healthcare handling dynamic context management • Augmented reality, Motion detection ...
Social Media and Crowdsourcing
Social media and crowdsourcing are important tools for solving complex problems. The benefit of crowdsourcing is that it leverages the power of human intelligence cost effectively and with less time. Social Media and Crowdsourcing: Application and Analytics examines the concepts of social media and crowdsourcing as well as their analytical aspects. It explores how these technologies contribute to the real world and examines such applications as promoting social good, agriculture, healthcare, tourism, disaster management, education, crime control, and cultural heritage. The book also looks at ethical issues in crowdsourcing and future scenarios and challenges for policy. Highlights of the boo...
Edge Computational Intelligence for AI-Enabled IoT Systems
Edge computational intelligence is an interface between edge computing and artificial intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems. Together, these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs ...
Trends of Artificial Intelligence and Big Data for E-Health
This book aims to present the impact of Artificial Intelligence (AI) and Big Data in healthcare for medical decision making and data analysis in myriad fields including Radiology, Radiomics, Radiogenomics, Oncology, Pharmacology, COVID-19 prognosis, Cardiac imaging, Neuroradiology, Psychiatry and others. This will include topics such as Artificial Intelligence of Thing (AIOT), Explainable Artificial Intelligence (XAI), Distributed learning, Blockchain of Internet of Things (BIOT), Cybersecurity, and Internet of (Medical) Things (IoTs). Healthcare providers will learn how to leverage Big Data analytics and AI as methodology for accurate analysis based on their clinical data repositories and c...
Innovations and Applications of Technology in Language Education
The linguistics and language education world has recently experienced a rapidly proliferating interest in applying technology. This interdisciplinary area bridges the gap between two previously separate fields. Innovations and Applications of Technology in Language Education is a collection of 12 chapters by an international group of language and linguistics education experts. Although technology in language education is a global interest, its practices should be contextualized. This book covers how language educational technology is currently applied, discusses how it should be applied, and gives directions for its future development. Providing a critical review of respective current practi...
Data-Driven Modelling and Predictive Analytics in Business and Finance
Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance co...
AI and IoT Technology and Applications for Smart Healthcare Systems
In recent years, the application of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart healthcare has been increasing. We are approaching a world where connected smart devices tell people when they need to visit a doctor because these devices will be able to detect health problems and discover symptoms of illness that may need medical care. AI-collaborative IoT technologies can help medical professionals with decision-making. These technologies can also help develop a sustainable and smart healthcare system. AI and IoT Technology and Applications for Smart Healthcare Systems helps readers understand complex scientific topics in a simple and accessible way. It int...
Deep Learning Applications in Operations Research
The model-based approach for carrying out the classification and identification of tasks has led to progression of the machine learning paradigm in diversified fields of technology. Deep Learning Applications in Operations Research presents the varied applications of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomenon. Such fields as object classification, speech recognition, and face detection have sought extensive applications of artificial intelligence (AI) and machine learning as well. The application of AI and ML has also become increasingly common in the domains ...
