Demystifying Big Data And Machine Learning For Healthcare
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Demystifying Big Data And Machine Learning For Healthcare
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Author : Prashant Natarajan
language : en
Publisher: CRC Press
Release Date : 2017-02-15
Demystifying Big Data And Machine Learning For Healthcare written by Prashant Natarajan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-15 with Medical categories.
Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.
Demystifying Big Data Machine Learning And Deep Learning For Healthcare Analytics
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Author : Pradeep N
language : en
Publisher: Academic Press
Release Date : 2021-06-10
Demystifying Big Data Machine Learning And Deep Learning For Healthcare Analytics written by Pradeep N and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-10 with Science categories.
Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. - Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies - Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics - Unique case study approach provides readers with insights for practical clinical implementation
Demystifying Big Data And Machine Learning For Healthcare
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Author : John C. Frenzel
language : en
Publisher:
Release Date : 2017
Demystifying Big Data And Machine Learning For Healthcare written by John C. Frenzel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
The Ethical Governance Of Artificial Intelligence And Machine Learning In Healthcare
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Author : Tina Nguyen
language : en
Publisher: Ethics International Press
Release Date : 2023-11-25
The Ethical Governance Of Artificial Intelligence And Machine Learning In Healthcare written by Tina Nguyen and has been published by Ethics International Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Medical categories.
This book explores the ethical governance of Artificial Intelligence (AI) & Machine Learning (ML) in healthcare. AI/ML usage in healthcare as well as our daily lives is not new. However, the direct, and oftentimes long-term effects of current technologies, in addition to the onset of future innovations, have caused much debate about the safety of AI/ML. On the one hand, AI/ML has the potential to provide effective and efficient care to patients, and this sways the argument in favor of continuing to use AI/ML; but on the other hand, the dangers (including unforeseen future consequences of the further development of the technology) leads to vehement disagreement with further AI/ML usage. Due to its potential for beneficial outcomes, the book opts to push for ethical AI/ML to be developed and examines various areas in healthcare, such as big data analytics and clinical decision-making, to uncover and discuss the importance of developing ethical governance for AI/ML in this setting.
Practical Applications Of Data Processing Algorithms And Modeling
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Author : Whig, Pawan
language : en
Publisher: IGI Global
Release Date : 2024-04-29
Practical Applications Of Data Processing Algorithms And Modeling written by Whig, Pawan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Computers categories.
In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.
Machine Learning For Healthcare
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Author : Rasit Dinc
language : en
Publisher: Troubador Publishing Ltd
Release Date : 2024-07-23
Machine Learning For Healthcare written by Rasit Dinc and has been published by Troubador Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-23 with Technology & Engineering categories.
Authored by a leading voice in the field, Machine Learning for Healthcare provides a gateway to revolutionize the understanding of medicine and patient care.
Application Of Machine Learning In Health Care Sector
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Author : Dr. Bharat Bhushan,
language : en
Publisher: Blue Rose Publishers
Release Date : 2022-11-02
Application Of Machine Learning In Health Care Sector written by Dr. Bharat Bhushan, and has been published by Blue Rose Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-02 with Health & Fitness categories.
Predictive Data Modelling For Biomedical Data And Imaging
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Author : Poonam Tanwar
language : en
Publisher: CRC Press
Release Date : 2024-09-13
Predictive Data Modelling For Biomedical Data And Imaging written by Poonam Tanwar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-13 with Computers categories.
In this book, we embark on a journey into the realm of predictive data modeling for biomedical data and imaging in healthcare. It explores the potential of predictive analytics in the field of medical science through utilizing various tools and techniques to unravel insights and enhance patient care. This volume creates a medium for an interchange of knowledge from expertise and concerns in the field of predictive data modeling. In detail, the research work on this will include the effective use of predictive data modeling algorithms to run image analysis tasks for understanding. Predictive Data Modelling for Biomedical Data and Imaging is divided into three sections, namely Section I – Beginning of Predictive Data Modeling for Biomedical Data and Imaging/Healthcare, Section II – Data Design and Analysis for Biomedical Data and Imaging/Healthcare, and Section III – Case Studies of Predictive Analytics for Biomedical Data and Imaging/Healthcare. We hope this book will inspire further research and innovation in the field of predictive data modeling for biomedical data and imaging in healthcare. By exploring diverse case studies and methodologies, this book contributes to the advancement of healthcare practices, ultimately improving patient outcomes and well-being.
Handbook On Augmenting Telehealth Services
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Author : Sonali Vyas
language : en
Publisher: CRC Press
Release Date : 2024-01-30
Handbook On Augmenting Telehealth Services written by Sonali Vyas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-30 with Computers categories.
Handbook on Augmenting Telehealth Services: Using Artificial Intelligence provides knowledge of AI-empowered telehealth systems for efficient healthcare services. The handbook discusses novel innovations in telehealth using AI techniques and also focuses on emerging tools and techniques in smart health systems. The book highlights important topics such as remote diagnosis of patients and presents e-health data management showcasing smart methods that can be used to improvise healthcare support and services. The handbook also shines a light on future trends in AI-enabled telehealth systems. Features Provides knowledge of AI-empowered telehealth systems for efficient healthcare services Discusses novel innovations in telehealth using AI techniques Covers emerging tools and techniques in smart health systems Highlights remote diagnosis of patients Focuses on e-health data management and showcases smart methods used to improvise healthcare support and services Shines a light on future trends in AI-enabled telehealth systems Every individual (patients, doctors, healthcare staff, etc.) is currently getting adapted to this new evolution of healthcare. This handbook is a must-read for students, researchers, academicians, and industry professionals working in the field of artificial intelligence and its uses in the healthcare sector.
Health Informatics Practical Guide Seventh Edition
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Author : William R. Hersh
language : en
Publisher: Lulu.com
Release Date : 2018
Health Informatics Practical Guide Seventh Edition written by William R. Hersh and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Science categories.
Health informatics is the discipline concerned with the management of healthcare data and information through the application of computers and other information technologies. The field focuses more on identifying and applying information in the healthcare field and less on the technology involved. Our goal is to stimulate and educate healthcare and IT professionals and students about the key topics in this rapidly changing field. This seventh edition reflects the current knowledge in the topics listed below and provides learning objectives, key points, case studies and extensive references. Available as a paperback and eBook. Visit the textbook companion website at http://informaticseducation.org for more information.--Page 4 de la couverture.