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    Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

    €143.75
    The book incorporates the many facets of computational intelligence, such as machine learning and deep learning, to provide groundbreaking developments in healthcare applications. It discusses theory, analytical methods, numerical simulation, scientific techniques, analytical outcomes, and computational structuring.
    ISBN: 9781032126876
    AuthorJena, Om Prakash (Ravenshaw University,
    SubAuthor1Bhushan, Bharat (Sharda University, Indi
    SubAuthor2Kose, Utku (Suleyman Demirel University,
    Pub Date25/02/2022
    BindingHardback
    Pages280
    AvailabilityCurrently out of stock. If available, delivery is usually 5-10 working days.
    Availability: Out of Stock

    Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.


    This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems.


    Features:










    Covers the fundamentals of ML and DL in the context of healthcare applications







    Discusses various data collection approaches from various sources and how to use them in ML/DL models







    Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field







    Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics







    Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly







    This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios.


    Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India.


    Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India.


    Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.

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    Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.


    This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems.


    Features:










    Covers the fundamentals of ML and DL in the context of healthcare applications







    Discusses various data collection approaches from various sources and how to use them in ML/DL models







    Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field







    Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics







    Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly







    This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios.


    Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India.


    Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India.


    Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.