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in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex;
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Intermediate user level;...
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This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible;
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prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI and Mathematical;
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Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for;
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conditions affected by COVID-19 pose new challenges for healthcare management and learning how to apply AI will be important for a broad spectrum;
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a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new;
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Artificial Intelligence and Machine Learning in Business Management The focus of this book is to introduce artificial intelligence (AI;
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, unsupervised, reinforcement, and evolutionary learning methods. * Introduces the similarity principle and related AI methods for both big and small;
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ENABLING HEALTHCARE 4.0 for PANDEMICS The book explores the role and scope of AI, machine learning and other current technologies to handle;
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machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and;
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Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data;
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Advances in smart healthcare systems (SHS) and artificial intelligence (AI) domains highlight the need for ICT systems that aim not only to;
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?and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem;
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This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public;
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A primer to AI and Machine Learning which also touches upon "good" and "bad" AI and its relationship with governments and corporations.;
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everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects;
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learning how to diagnose problems as ones that can and cannot be solved with AI. You'll then learn the basics of computer science algorithms;
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Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning;
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any online entitlements included with the product. The first surgical AI guide of its kind! Machine learning, neural networks, and computer;
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research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare;
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Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very;
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methods for addressing marketing and sales problems will benefit most if they are exposed to how AI and machine learning have been applied;
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toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data;
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Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies;
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to build AI solutions for images, text, sounds, and images Implement NLP, reinforcement learning, deep learning, GANs, Monte-Carlo tree;
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, hybrid models, machine learning, meta heuristics, neuro fuzzy system, and optimization principles. The book acts as a reference book for AI;
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