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Deep Learning for Cancer Diagnosis
This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.
Deep Learning for Medical Decision Support Systems
This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.
Artificial Intelligence
This book provides an examination of cutting-edge research and developments in the field of artificial intelligence. It seeks to extend the view in both technical and societal evaluations to ensure a well-defined balance for societal outcomes. It explores hot topics such as generative artificial intelligence, artificial intelligence in law, education, and climate change. Artificial Intelligence: Technical and Societal Advancements seeks to bridge the gap between theory and practical applications of AI by giving readers insight into recent advancements. It offers readers a deep dive into the transformative power of AI for the present and future world. As artificial intelligence continues to r...
ICASISET 2020
We are delighted to introduce the proceedings of the first edition of the 2020 European Alliance for Innovation (EAI) International Conference on Advanced Scientific Innovation in Science, Engineering and Technology. This conference has brought innovative academics, industrial experts researchers, developers and practitioners around the world in the field of Science, Engineering and Technology to a common forum. The technical program of ICASISET 2020 consisted of 97 full papers, including 6 invited papers in oral presentation sessions at the main conference tracks. The conference tracks were: Innovative Computing, Advanced innovation technology in Communication, Industry automation, hydrogen...
Metaheuristic and Evolutionary Computation: Algorithms and Applications
This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book’s second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.
Social Media: The Good, the Bad, and the Ugly
This book constitutes the refereed conference proceedings of the 15th IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2016, held in Swansea, UK, in September 2016 The 47 full and 17 short papers presented were carefully reviewed and selected from 90 submissions. They are organized in the following topical sections: social media strategy and digital business; digital marketing and customer relationship management; adoption and diffusion; information sharing on social media; impression, trust, and risk management; data acquisition, management and analytics; e-government and civic engagement; e-society and online communities.
Cyber Warfare, Security and Space Research
This book sonstitutes selected papers from the first International Conference on Cyber Warfare, Security and Space Research, SpacSec 2021, held in Jaipur, India, in December 2021. The 19 full and 6 short papers were thoroughly reviewed and selected from the 98 submissions. The papers present research on cyber warfare, cyber security, and space research area, including the understanding of threats and risks to systems, the development of a strong innovative culture, and incident detection and post-incident investigation.
Green Building Management and Smart Automation
Throughout the world, there is an increasing demand on diminishing natural resources in the industrial, transport, commercial, and residential sectors. Of these, the residential sector uses the most energy on such needs as lighting, water heating, air conditioning, space heating, and refrigeration. This sector alone consumes one-third of the total primary energy resources available. By using green building and smart automation techniques, this demand for energy resources can be lowered. Green Building Management and Smart Automation is an essential scholarly publication that provides an in-depth analysis of design technologies for green building and highlights the smart automation technologies that help in energy conservation, along with various performance metrics that are necessary to facilitate a building to be known as a “Green Smart Building.” Featuring a range of topics such as environmental quality, energy management, and big data analytics, this book is ideal for researchers, engineers, policymakers, government officials, architects, and students.
