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This book focuses on recent technological advances in digital dentistry. It provides information on digital aspects in all dental fields including digital caries detection systems, digital color matching, and digital applications in periodontology, surgical implant placement, oral histopathology and pediatric dentistry. Training in emerging and new digital techniques is inevitable in the dental profession. This book contains detailed digital procedures, their basics and their applications. It is divided into three parts: Basic Digital Systems in Dentistry, Novelties and Advances in Digital Dentistry, The Future of Digital Dentistry and Applications. Readers will learn about Artificial Intelligence in dentistry, tissue engineering applications and dental education tools in digital dentistry. The book is a must have for all dental practitioners who would like to deepen their knowledge and understanding of digital systems in dentistry.

Dentistry. --- Dental informatics.

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This book delves into practical implementation of evolutionary and metaheuristic algorithms to advance the capacity of machine learning. The readers can gain insight into the capabilities of data-driven evolutionary optimization in materials mechanics, and optimize your learning algorithms for maximum efficiency. Or unlock the strategies behind hyperparameter optimization to enhance your transfer learning algorithms, yielding remarkable outcomes. Or embark on an illuminating journey through evolutionary techniques designed for constructing deep-learning frameworks. The book also introduces an intelligent RPL attack detection system tailored for IoT networks. Explore a promising avenue of optimization by fusing Particle Swarm Optimization with Reinforcement Learning. It uncovers the indispensable role of metaheuristics in supervised machine learning algorithms. Ultimately, this book bridges the realms of evolutionary dynamic optimization and machine learning, paving the way for pioneering innovations in the field.

Machine learning. --- Medical informatics. --- Machine Learning. --- Health Informatics.

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This book constitutes the refereed post-conference proceedings of the 6th EAI International Conference Computer on Science and Engineering in Health Services (COMPSE 2022), which took place in Mexico City and online, June 28th, 2022. The papers are grouped on thematic topics: application of tools delivered by the COVID-19 pandemic; health services; computer and data science; and industry 4.0 in logistics and supply chain. The content is relevant to researchers, academics, students and professionals. Presents the proceedings of the 6th EAI International Conference on Computer Science and Engineering in Health Services (COMPSE 2022); Includes topics such as computer and data science, AI tools and applications, and machine learning for optimization; Relevant to researchers, academics, students and professionals in communications engineering.

Telecommunication. --- Medical informatics. --- Application software. --- Communications Engineering, Networks. --- Health Informatics. --- Computer and Information Systems Applications.

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This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls is a comprehensive guide to how AI and ML techniques can best be applied in health care. The emphasis placed on how to avoid a variety of pitfalls that can be encountered makes it an indispensable guide for all medical informatics professionals and physicians who utilize these methodologies on a day-to-day basis. Furthermore, this work will be of significant interest to health data scientists, administrators and to students in the health sciences seeking an up-to-date resource on the topic.

Medical informatics. --- Medical care. --- Bioinformatics. --- Public health. --- Health Informatics. --- Health Care. --- Public Health.

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Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles current research on Artificial Intelligence within medical subspecialties, helping practitioners with diagnosis, clinical decision-making, disease prediction, prevention, and the facilitation of precision medicine. The book defines the basic concepts of big data and AI in medicine and highlights current applications, challenges, ethical issues, and biases. Each chapter discusses AI applied to a specific medical subspecialty, including primary care, preventive medicine, general internal medicine, radiology, pathology, infectious disease, gastroenterology, cardiology, hematology, oncology, dermatology, ophthalmology, mental health, neurology, pulmonary, critical care, rheumatology, surgery, and OB-GYN. This is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested in learning more about artificial intelligence technologies and their applications in medicine.

Application software. --- Artificial intelligence. --- Data mining. --- Artificial intelligence --- Medical informatics. --- Clinical trials --- Artificial Intelligence --- Medical informatics --- Medical Informatics Computing --- Clinical Medicine --- Medical applications. --- Data processing.