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Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance. This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools. The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance.
This book gives a complete presentatin of the basic essentials of machinery prognostics and prognosis oriented maintenance management, and takes a look at the cutting-edge discipline of intelligent failure prognosis technologies for condition-based maintenance. Presents an introduction to advanced maintenance systems, and discusses the key technologies for advanced maintenance by providing readers with up-to-date technologies Offers practical case studies on performance evaluation and fault diagnosis technology, fault prognosis and remaining useful life prediction and maintenance scheduling, enhancing the understanding of these technologies Pulls togeter recent developments and varying methods into one volume, complemented by practical examples to provide a complete reference
An analysis of different concepts and case studies in engineering disciplines such as chemical, civil, electrical, telecommunications and mechanical engineering, demonstrating how engineering systems and processes can leverage the power of AI to drive and achieve the UN SDGs.
The first report in a new flagship series, WIPO Technology Trends, aims to shed light on the trends in innovation in artificial intelligence since the field first developed in the 1950s.
The manufacturing industry is a cornerstone of national economy and people’s livelihood. It is the way of transforming resources into products or goods which are required to cater to the needs of the society. Traditional manufacturing companies currently face several challenges such as rapid technological changes, inventory problem, shortened innovation, short product life cycles, volatile demand, low prices, highly customized products, and ability to compete in the global markets. Modern manufacturing is highly competitive due to globalization and fast changes in the global market. This book reviews emerging technologies in manufacturing. These technologies include artificial intelligence, smart manufacturing, lean manufacturing, robotics, automation, 3D printing, nanotechnology, industrial Internet of things, and augmented reality. The use of these technologies will have a profound impact on the manufacturing industry. The book consists of 19 chapters. Each chapter addresses a single emerging technology in depth and describes how manufacturing organizations are adopting the technology. The book fills an important niche for manufacturing. It is a comprehensive, jargon-free introductory text on the issues, ideas, theories, and problems on emerging technologies in manufacturing. It is a must-read book for beginners or anyone who wants to be updated about emerging technologies.
Software is the essential enabling means for science and the new economy. It helps us to create a more reliable, flexible and robust society. But software often falls short of our expectations. Current methodologies, tools, and techniques remain expensive and are not yet sufficiently reliable, while many promising approaches have proved to be no more than case-by-case oriented methods. This book contains extensively reviewed papers from the thirteenth International Conference on New Trends in software Methodology, Tools and Techniques (SoMeT_14), held in Langkawi, Malaysia, in September 2014. The conference provides an opportunity for scholars from the international research community to discuss and share research experiences of new software methodologies and techniques, and the contributions presented here address issues ranging from research practices and techniques and methodologies to proposing and reporting solutions for global world business. The emphasis has been on human-centric software methodologies, end-user development techniques and emotional reasoning, for an optimally harmonized performance between the design tool and the user. Topics covered include the handling of cognitive issues in software development to adapt it to the user's mental state and intelligent software design in software utilizing new aspects on conceptual ontology and semantics reflected on knowledge base system models. This book provides an opportunity for the software science community to show where we are today and where the future may take us.