Demystifying Big Data and Machine Learning for Healthcare Book

Demystifying Big Data and Machine Learning for Healthcare


  • Author : Prashant Natarajan
  • Publisher : CRC Press
  • Release Date : 2017-02-15
  • Genre: Medical
  • Pages : 210
  • ISBN 10 : 9781315389318

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Demystifying Big Data and Machine Learning for Healthcare Excerpt :

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 Book

Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics


  • Author : Pradeep N
  • Publisher : Academic Press
  • Release Date : 2021-06-25
  • Genre: Science
  • Pages : 372
  • ISBN 10 : 9780128220443

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Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics Excerpt :

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

Digital Health Transformation with Blockchain and Artificial Intelligence Book

Digital Health Transformation with Blockchain and Artificial Intelligence


  • Author : Chinmay Chakraborty
  • Publisher : CRC Press
  • Release Date : 2022-05-11
  • Genre: Technology & Engineering
  • Pages : 368
  • ISBN 10 : 9781000580945

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Digital Health Transformation with Blockchain and Artificial Intelligence Excerpt :

The book Digital Health Transformation with Blockchain and Artificial Intelligence covers the global digital revolution in the field of healthcare sector. The population has been overcoming the COVID-19 period; therefore, we need to establish intelligent digital healthcare systems using various emerging technologies like Blockchain and Artificial Intelligence. Internet of Medical Things is the technological revolution that has included the element of "smartness" in the healthcare industry and also identifying, monitoring, and informing service providers about the patient’s clinical information with faster delivery of care services. This book highlights the important issues i.e. (a) How Internet of things can be integrated with the healthcare ecosystem for better diagnostics, monitoring, and treatment of the patients, (b) Artificial Intelligence for predictive and preventive healthcare systems, (c) Blockchain for managing healthcare data to provide transparency, security, and distributed storage, and (d) Effective remote diagnostics and telemedicine approach for developing smart care. The book encompasses chapters belong to the blockchain, Artificial Intelligence, and Big health data technologies. Features: Blockchain and internet of things in healthcare systems Secure Digital Health Data Management in Internet of Things Public Perception towards AI-Driven Healthcare Security, privacy issues and challenges in adoption of smart digital healthcare Big data analytics and Internet of things in the pandemic era Clinical challenges for digital health revolution Artificial intelligence for advanced healthcare Future Trajectory of Healthcare with Artificial Intelligence 9 Parkinson disease pre-diagnosis using smart technologies Emerging technologies to combat the COVID-19 Machine Learning and Internet of Things in Digital Health Transformation Effective Remote Healthcare and Telemedicine Approaches Legal implication of blockchain technology in public health This Book on "D

Intelligent Healthcare Book

Intelligent Healthcare


  • Author : Chinmay Chakraborty
  • Publisher : Springer Nature
  • Release Date : 2022-07-07
  • Genre: Uncategoriezed
  • Pages : null
  • ISBN 10 : 9789811681509

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Intelligent Healthcare Excerpt :

Emerging Technologies in Healthcare Book

Emerging Technologies in Healthcare


  • Author : Matthew N. O. Sadiku
  • Publisher : AuthorHouse
  • Release Date : 2021-10-05
  • Genre: Medical
  • Pages : 316
  • ISBN 10 : 9781665528429

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Emerging Technologies in Healthcare Excerpt :

Health is regarded as one of the global challenges for mankind. Healthcare is a complex system that covers processes of diagnosis, treatment, and prevention of diseases. It constitutes a fundamental pillar of the modern society. Modern healthcare is technological healthcare. Technology is everywhere. This book focuses on twenty-one emerging technologies in the healthcare industry. An emerging technology is one that holds the promise of creating a new economic engine and is trans-industrial. Emerging technological trends are rapidly transforming businesses in general and healthcare in particular in ways that we find hard to imagine. Artificial intelligence (AI), machine learning, robots, blockchain, cloud computing, Internet of things (IoT), and augmented & virtual reality are some of the technologies at the heart of this revolution and are covered in this book. The convergence of these technologies is upon us and will have a huge impact on the patient experience

Machine Learning with Health Care Perspective Book

Machine Learning with Health Care Perspective


  • Author : Vishal Jain
  • Publisher : Springer Nature
  • Release Date : 2020-03-09
  • Genre: Technology & Engineering
  • Pages : 415
  • ISBN 10 : 9783030408503

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Machine Learning with Health Care Perspective Excerpt :

This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.

Demystifying AI for the Enterprise Book

Demystifying AI for the Enterprise


  • Author : Prashant Natarajan
  • Publisher : CRC Press
  • Release Date : 2021-12-31
  • Genre: Computers
  • Pages : 434
  • ISBN 10 : 9781351032926

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Demystifying AI for the Enterprise Excerpt :

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

Intelligence Based Medicine Book

Intelligence Based Medicine


  • Author : Anthony C. Chang
  • Publisher : Academic Press
  • Release Date : 2020-06-27
  • Genre: Medical
  • Pages : 534
  • ISBN 10 : 9780128233382

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Intelligence Based Medicine Excerpt :

Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics Book

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics


  • Author : Abhishek Kumar
  • Publisher : CRC Press
  • Release Date : 2022
  • Genre: Technology & Engineering
  • Pages : 224
  • ISBN 10 : 1003132111

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Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics Excerpt :

"In the last two decades, machine learning has been dramatically developed and is still experiencing a fast and ever-lasting change in paradigm, methodology, applications, and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on the diversity and complexity. Machine Learning Approaches and Applications Applied Intelligence for Healthcare Data Analytics presents a variety of techniques design to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design, along with interdisciplinary challenges. This book is useful to research scholars and students involved in critical condition analysis and computation models"--

Information and Communication Technologies for Development Evaluation Book

Information and Communication Technologies for Development Evaluation


  • Author : Oscar A. García
  • Publisher : Routledge
  • Release Date : 2019-07-09
  • Genre: Business & Economics
  • Pages : 158
  • ISBN 10 : 9780429650543

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Information and Communication Technologies for Development Evaluation Excerpt :

Written by a team of expert practitioners at the Independent Office of Evaluation of International Fund for Agricultural Development (IFAD), this book gives an insight into the implications of new and emerging technologies in development evaluation. Growing technologies such as big data analytics, machine learning and remote sensing present new opportunities for development practitioners and development evaluators, particularly when measuring indicators of the Sustainable Development Goals. The volume provides an overview of information and communication technologies (ICTs) in the context of evaluation, looking at the theory and practice, and discussing how the landscape may unfold. It also considers concerns about privacy, ethics and inclusion, which are crucial issues for development practitioners and evaluators working in the interests of vulnerable populations across the globe. Among the contributions are case studies of seven organizations using various technologies for data collection, analysis, dissemination and learning. This valuable insight into practice will be of interest to researchers, practitioners and policymakers in development economics, development policy and ICT.

Artificial Intelligence in Healthcare Book

Artificial Intelligence in Healthcare


  • Author : Adam Bohr
  • Publisher : Academic Press
  • Release Date : 2020-06-21
  • Genre: Computers
  • Pages : 378
  • ISBN 10 : 9780128184394

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Artificial Intelligence in Healthcare Excerpt :

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

A Global Approach to Data Value Maximization Book

A Global Approach to Data Value Maximization


  • Author : Paolo Dell’Aversana
  • Publisher : Cambridge Scholars Publishing
  • Release Date : 2019-04-17
  • Genre: Computers
  • Pages : 226
  • ISBN 10 : 9781527533370

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A Global Approach to Data Value Maximization Excerpt :

This book presents a systematic discussion about methods and techniques used to extract the maximum informative value from complex data sets. A multitude of approaches and techniques can be applied for that purpose, including data fusion and model integration, multimodal data analysis in different physical domains, audio-video display of data through techniques of “sonification”, multimedia machine learning, and hybrid methods of data analysis. The book begins with the domain of geosciences, before moving on to other scientific areas, like diagnostic medicine and various engineering sectors. As such, it will appeal to a large audience, including geologists and geophysicists, data scientists, physicians and cognitive scientists, and experts in social sciences and knowledge management.

Machine Learning for Healthcare Book

Machine Learning for Healthcare


  • Author : Rashmi Agrawal
  • Publisher : CRC Press
  • Release Date : 2020-12-08
  • Genre: Computers
  • Pages : 204
  • ISBN 10 : 9781000221787

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Machine Learning for Healthcare Excerpt :

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.

Advances in Surgery 2020 Book

Advances in Surgery 2020


  • Author : John L. Cameron
  • Publisher : Elsevier Health Sciences
  • Release Date : 2020-08-30
  • Genre: Medical
  • Pages : 240
  • ISBN 10 : 9780323755245

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Advances in Surgery 2020 Excerpt :

Each year, Advances in Surgery reviews the most current practices in general surgery. A distinguished editorial board, headed by Dr. John Cameron, identifies key areas of major progress and controversy and invites preeminent specialists to contribute original articles devoted to these topics. These insightful overviews in general surgery bring concepts to a clinical level and explore their everyday impact on patient care.

Research Anthology on Telemedicine Efficacy  Adoption  and Impact on Healthcare Delivery Book

Research Anthology on Telemedicine Efficacy Adoption and Impact on Healthcare Delivery


  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release Date : 2021-01-15
  • Genre: Medical
  • Pages : 689
  • ISBN 10 : 9781799881070

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Research Anthology on Telemedicine Efficacy Adoption and Impact on Healthcare Delivery Excerpt :

Telemedicine, which involves electronic communications and software, provides the same clinical services to patients without the requirement of an in-person visit. Essentially, this is considered remote healthcare. Though telemedicine is not a new practice, it has become an increasingly popular form of healthcare delivery due to current events, including the COVID-19 pandemic. Not only are visits being moved onto virtual platforms, but additional materials and correspondence can remain in the digital sphere. Virtual lab results, digital imaging, medical diagnosis, and video consultations are just a few examples that encompass how telemedicine can be used for increased accessibility in healthcare delivery. With telemedicine being used in both the diagnosis and treatment of patients, technology in healthcare can be implemented at almost any phase of the patient experience. As healthcare delivery follows the digital shift, it is important to understand the technologies, benefits and challenges, and overall impacts of the remote healthcare experience. The Research Anthology on Telemedicine Efficacy, Adoption, and Impact on Healthcare Delivery presents the latest research on best practices for adopting telehealth into medical practices and its efficacy and solutions for the improvement of telemedicine, as well as addresses emerging challenges and opportunities, including issues such as securing patient data and providing healthcare accessibility to rural populations. Covering important themes that include doctor-patient relationships, tele-wound monitoring, and telemedicine regulations, this book is essential for healthcare professionals, doctors, medical students, academic and medical libraries, medical technologists, practitioners, stakeholders, researchers, academicians, and students interested in the emerging technological developments and solutions within the field of telemedicine.