Smart Healthcare for Disease Diagnosis and Prevention Books

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Smart Healthcare for Disease Diagnosis and Prevention


Smart Healthcare for Disease Diagnosis and Prevention
  • Author : Sudip Paul
  • Publisher : Academic Press
  • Release : 2020-01-14
  • ISBN : 9780128179147
  • Language : En, Es, Fr & De
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Smart Healthcare for Disease Diagnosis and Prevention focuses on the advancement in healthcare technology to improve human health at all levels using smart technologies. It covers all necessary topics from basic concepts (such as signal and image processing) to advanced knowledge on topics such as tissue engineering, virtual and intelligent instrumentation (or VLSI) and Embedded Systems. This book can be used to guide students and young researchers, providing basic knowledge on signal/image processing and smart technologies. Users will find a perfect blend of the interdisciplinary approach to biomedical engineering. The book considers many technical concepts, emerging technologies, real-world healthcare applications, and many other technical, multidisciplinary notions in the same content. Finally, it systemically introduces the technologies and devices for healthcare objects and targets disease diagnosis and prevention in different views. Discusses how new advanced technologies are used in real healthcare applications to improve patient safety Explores how medical data such as signals and images can be used in diagnosis Covers how wireless communications devices, such as sensor networks, RFID, wireless body area network, and wearable sensors are used in the medical environment

Mobile Health Advances in Research and Applications


Mobile Health  Advances in Research and Applications
  • Author : Gaurav Gupta
  • Publisher :
  • Release : 2021-06-10
  • ISBN : 1536194204
  • Language : En, Es, Fr & De
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Smart health technologies continue to gain research interest across the globe in this digital era. Researchers are focusing on advancements in healthcare systems to make human life better. Also, such advancements help in early disease diagnosis and prevention of the worst diseases. Designing smart healthcare systems is possible only because of recent developments in artificial intelligence, machine learning and IoT technologies. Though mHealth refers to all mobile devices which can communicate data, mobile phones are presently the most popular platform for mHealth delivery. Ninety-four percent of the world population owns/uses a mobile phone, making mobile phones an optimal delivery platform for mHealth interventions. mHealth may catalyse the healthcare delivery model from a historical/episodic model into a tangible/patient-centric model. mHealth is being viewed progressively by many as an essential technology metaphor to achieve rich, vigorous patient engagement, ultimately achieving a patient-centric paradigm change.This book will discuss diverse topics to explain the rapidly emerging and evolving mobile health and artificial perspective, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various research domains. It presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of as well as the hindrances to mHealth. The wide variety in topics it presents offers readers multiple perspectives on a variety of disciplines.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 readers to grasp the extensive point of view and the essence of recent advances in this field. This book solicits contributions which include theory, case studies and computing paradigms pertaining to 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 from both theoretical and practical viewpoints to spur further advances in the field. A brief introduction about each chapter follows. Chapter 1 focuses on the role of Internet of Things (IoT) technologies in healthcare which provides an overview of the various types of IoT devices and data generating equipment for medical information.In Chapter 2, the objective is to provide a brief discussion about the advantages and disadvantages of using IoT based technologies in healthcare such as wearable devices. Chapter 3 deals with important aspects of data science for healthcare systems, which includes various algorithms for decision support system algorithms. Chapter 4 discusses various innovative technologies like digital twins for healthcare and medical diagnosis.Chapter 5 discusses research investigating the long-term effects of pregnancy and lactation on the female body.Chapter 6 summarizes recent advances in machine and deep learning techniques for smart healthcare applications.Chapter 7 explores the research insights on using an artificial neural network with a wrapper-based feature selection to predict heart failure.Chapter 8 presents a review on context-aware mobile healthcare for smart health services in nursing homes.Chapter 9 focuses on certain machine learning methods that can help in early prediction of pandemics.Chapter 10 explores techniques and methods based on machine learning for malaria diagnosis.Chapter 11 is a complete discussion about mobile health technology to improve health-related quality of life of chronic disease patients in emerging economies.We are grateful to the authors and reviewers for their excellent contributions for making this book possible.

Computational Intelligence in Healthcare


Computational Intelligence in Healthcare
  • Author : Amit Kumar Manocha
  • Publisher : Springer Nature
  • Release :
  • ISBN : 9783030687236
  • Language : En, Es, Fr & De
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Computing Paradigms for Smart Healthcare


Computing Paradigms for Smart Healthcare
  • Author : B. Vinoth Kumar
  • Publisher :
  • Release : 2020-11-20
  • ISBN : 1536186198
  • Language : En, Es, Fr & De
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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 learningChapter 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.

Improving Diagnosis in Health Care


Improving Diagnosis in Health Care
  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release : 2016-01-29
  • ISBN : 9780309377690
  • Language : En, Es, Fr & De
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Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001) finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.