Om prakash jena (118 Ergebnisse)

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paperback. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

paperback. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

paperback. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Paperback. Zustand: New. 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.…

Paperback. Zustand: New. The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedicalPresents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical scienceDiscusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applicationsCovers algorithms, tools, and frameworks for explainable artificial intelligence on medical dataExplores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processingDiscusses machine learning and deep learning scalability models in healthcare systemsThis text focuses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering. …

Paperback. Zustand: New. The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications.FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analyticsThis book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.…

Paperback. Zustand: Brand New. 204 pages. 9.18x6.12x9.21 inches. In Stock.