Applied Smart Health Care Informatics

Applied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new research directions and highlight the smart technologies that are central to establishing proactive health management, supporting enhanced coordination of care, and improving the overall quality of healthcare services. Provides an overview of different deep learning applications for intelligent healthcare informatics management Describes novel methodologies and emerging trends in artificial intelligence and computational intelligence and their relevance to health information engineering and management Proposes IoT solutions that disseminate essential medical information for intelligent healthcare management Discusses mobile-based healthcare management, content-based image retrieval, and computer-aided diagnosis using machine and deep learning techniques Examines the use of exploratory data analysis in intelligent healthcare informatics systems Applied Smart Health Care Informatics: A Computational Intelligence Perspective is an invaluable text for graduate students, postdoctoral researchers, academic lecturers, and industry professionals working in the area of healthcare and intelligent soft computing.

Innovation in Health Informatics: A Smart Healthcare Primer explains how the most recent advances in information and communication technologies have paved the way for new breakthroughs in healthcare. The book showcases current and prospective applications in a context defined by an imperative to deliver efficient, patient-centered and sustainable healthcare systems. Topics discussed include big data, medical data analytics, artificial intelligence, machine learning, virtual and augmented reality, 5g and sensors, Internet of Things, nanotechnologies and biotechnologies. Additionally, there is a discussion on social issues and policy- making for the implementation of smart healthcare. This book is a valuable resource for undergraduate and graduate students, practitioners, researchers, clinicians and data scientists who are interested in how to explore the intersections between bioinformatics and health informatics. Provides a holistic discussion on the new landscape of medical technologies, including big data, analytics, artificial intelligence, machine learning, virtual and augmented reality, 5g and sensors, Internet of Things, nanotechnologies and biotechnologies Presents a case study driven approach, with references to real-world applications and systems Discusses topics with a research-oriented approach that aims to promote research skills and competencies of readers

Applied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new research directions and highlight the smart technologies that are central to establishing proactive health management, supporting enhanced coordination of care, and improving the overall quality of healthcare services. Provides an overview of different deep learning applications for intelligent healthcare informatics management Describes novel methodologies and emerging trends in artificial intelligence and computational intelligence and their relevance to health information engineering and management Proposes IoT solutions that disseminate essential medical information for intelligent healthcare management Discusses mobile-based healthcare management, content-based image retrieval, and computer-aided diagnosis using machine and deep learning techniques Examines the use of exploratory data analysis in intelligent healthcare informatics systems Applied Smart Health Care Informatics: A Computational Intelligence Perspective is an invaluable text for graduate students, postdoctoral researchers, academic lecturers, and industry professionals working in the area of healthcare and intelligent soft computing.

"Smart healthcare has gradually gained its popularity because of the development of information technologies and computing paradigms such as internet of things (loT), big data, Cloud computing and artificial intelligence. These technologies transform the conventional medical system in to smarter one by making healthcare more convenient, efficient, accurate, and more customized. Smart healthcare will lead to a revolutionized healthcare system that enables the participation of all people for the early prediction and prevention of diseases so that preemptive and pro-active treatment can be delivered. The aim of this edited book is to publish the latest research advancements in the convergence of automation technology, artificial intelligence, biomedical engineering and health informatics. This will help the readers to grasp the extensive point of view and the essence of the recent advances in this field. This book solicits contributions which include theory, case studies and computing paradigms pertaining to the healthcare applications. The prospective audience would be researchers, professionals, practitioners, and students from academia and industry who work in this field. We hope the chapters presented will inspire future research both from theoretical and practical viewpoints to spur further advances in the field. The entire book is the contribution of interdisciplinary expertise available in the esteemed Institution PSG College of Technology, an ISO 9001:2015 certified Government aided Institution, belonging to Department of Information Technology, Computer Science and Engineering, Electronics and Communication Engineering, Biomedical Engineering and Biotechnology. A brief introduction about each chapter is as follows. Chapter 1 focuses on health informatics which provides an overview of the various types of data originating from the medical information, Chapter 2 objective is to provide a 'smart connected environment' which includes storing, processing and exchange information seamlessly using technologies. Chapter 3 deals with an intelligent healthcare system for automatic diagnosis of diseases based on IOT enabled cloud computing framework and deep learning Chapter 4 discuss about basic concepts of digital twin technology and implementation of digital twin in various health care domains. Chapter 5 proposes a graph based framework for classification, feature selection method which uses the existing notion, histograms for extracting isotonic features from a data set. Chapter 6 explains the significance of convolution neural network in medical image analysis. Chapter 7 summarizes recent advances in AI tools applied in cancer diagnosis and research for disease prediction and biomarker discovery. Chapter 8 explores DNA microarray data followed by the implementation of machine learning algorithms to obtain the highly predictive genes for classification. Chapter 9 uses various data structures such as hash tables and prefix-based search trees to efficiently query the EHR data present in the Blockchain. Chapter 10 focuses on agreeing upon a common symmetric cryptographic key generated from the ECG signal collected at different locations of a patient using linear prediction and error control coding techniques. We are grateful to the authors and reviewers for their excellent contributions for making this book possible"--

This book covers the fundamentals of IoT and healthcare systems for carrying out system architectures, protocols, wearable devices, and interoperability. It explores major challenges in artificial intelligence (AI) and smart computing in resource-constrained IoT-based applications along with cost, energy efficiency, and the availability of quality service. Healthcare Systems and Health Informatics: Using Internet of Things explores the role of AI and smart computing in health informatics and healthcare with an emphasis on clinical data management and analysis for precise prediction and prompt action. It presents cutting-edge tracking, monitoring, real-time assistance, and security for IoT in healthcare and broadly discusses wearable sensors and IoT devices and their role in smart living assistance. The book goes on to describe a system model and architecture for a clear picture of energy conservation–based IoT in healthcare and explains the challenges and opportunities with IoT-based healthcare industries. A study of the threats and impacts, along with the need for information security, is also included. The chapters are written by experts in the field, and this book provides a comprehensive description of the important aspects of IoT and health from a beginner- to advanced-level perspective and is ideal for researchers, academicians, students, persons in industry, technologists, and entrepreneurs.

The American Medical Informatics Association (AMIA) defines the term biomedical informatics (BMI) as: The interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health. This book: Applied Interdisciplinary Theory in Health Informatics: A Knowledge Base for Practitioners, explores the theories that have been applied in health informatics and the differences they have made. The editors, all proponents of evidence-based health informatics, came together within the European Federation of Medical Informatics (EFMI) Working Group on Health IT Evaluation and the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development. The purpose of the book, which has a foreword by Charles Friedman, is to move forward the agenda of evidence-based health informatics by emphasizing theory-informed work aimed at enriching the understanding of this uniquely complex field. The book takes the AMIA definition as particularly helpful in its articulation of the three foundational domains of health informatics: health science, information science, and social science and their various overlaps, and this model has been used to structure the content of the book around the major subject areas. The book discusses some of the most important and commonly used theories relevant to health informatics, and constitutes a first iteration of a consolidated knowledge base that will advance the science of the field.

Smart Computational Intelligence in Biomedical and Health Informatics presents state-of-art innovations, research, design, and implementation of methodological and algorithmic solutions to data processing problems, designing, including analysis of evolving trends in health informatics and computer-aided diagnosis. Further, it describes practical, applications-led research on the use of methods and devices in clinical diagnosis, disease prevention, patient monitoring and management. It covers simulation and modeling, measurement and control, analysis, information extraction and monitoring of physiological data in clinical medicine and the biological sciences. Covers evolutionary approaches to solve optimization problems in biomedical engineering. Discusses IoT, Cloud computing, data analytics in healthcare informatics. Provides computational intelligence-based solution for diagnosis of diseases. Reviews modelling and simulations in designing of biomedical equipment. Promotes machine learning based approaches to improvements in biomedical engineering problems. This book is aimed at researchers, graduate students in healthcare, biomedical engineering, health informatics, computational intelligence, and machine learning.

"An engaging introduction to an exciting multidisciplinary field where positive impact depends less on technology than on understanding and responding to human motivations, specific information needs, and life constraints." -- Betsy L. Humphreys, former Deputy Director, National Library of Medicine This is a book for people who want to design or promote information technology that helps people be more active and informed participants in their healthcare. Topics include patient portals, wearable devices, apps, websites, smart homes, and online communities focused on health. Consumer Healthcare Informatics: Enabling Digital Health for Everyone educates readers in the core concepts of consumer health informatics: participatory healthcare; health and e-health literacy; user-centered design; information retrieval and trusted information resources; and the ethical dimensions of health information and communication technologies. It presents the current state of knowledge and recent developments in the field of consumer health informatics. The discussions address tailoring information to key user groups, including patients, consumers, caregivers, parents, children and young adults, and older adults. For example, apps are considered as not just a rich consumer technology with the promise of empowered personal data management and connectedness to community and healthcare providers, but also a domain rife with concerns for effectiveness, privacy, and security, requiring both designer and user to engage in critical thinking around their choices. This book’s unique contribution to the field is its focus on the consumer and patient in the context of their everyday life outside the clinical setting. Discussion of tools and technologies is grounded in this perspective and in a context of real-world use and its implications for design. There is an emphasis on empowerment through participatory and people-centered care.