Health Monitoring And Personalized Feedback Using Multimedia Data
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Health Monitoring and Personalized Feedback using Multimedia Data by Alexia Briassouli,Jenny Benois-Pineau,Alexander Hauptmann Pdf
This book presents how multimedia data analysis, information retrieval and indexing are central for comprehensive, personalized, adaptive quality care and the prolongation of independent living at home. With sophisticated technologies in monitoring, diagnosis, and treatment, multimodal data plays an increasingly central role in healthcare. Experts in computer vision, image processing, medical imaging, biomedical engineering, medical informatics, physical education and motor control, visual learning, nursing and human sciences, information retrieval, content based image retrieval, eHealth, information fusion, multimedia communications and human computer interaction come together to provide a thorough overview of multimedia analysis in medicine and daily life.
Intelligent Healthcare Systems by Vania V. Estrela Pdf
The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems’ design practices and computational intelligence tactics for medical usage. The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.
Aging and Mental Health by Daniel L. Segal,Sara Honn Qualls,Michael A. Smyer Pdf
Fully updated and revised, this new edition of a highly successful text provides students, clinicians, and academics with a thorough introduction to aging and mental health. The third edition of Aging and Mental Health is filled with new updates and features, including the impact of the DSM-5 on diagnosis and treatment of older adults. Like its predecessors, it uses case examples to introduce readers to the field of aging and mental health. It also provides both a synopsis of basic gerontology needed for clinical work with older adults and an analysis of several facets of aging well. Introductory chapters are followed by a series of chapters that describe the major theoretical models used to understand mental health and mental disorders among older adults. Following entries are devoted to the major forms of mental disorders in later life, with a focus on diagnosis, assessment, and treatment issues. Finally, the book focuses on the settings and contexts of professional mental health practice and on emerging policy issues that affect research and practice. This combination of theory and practice helps readers conceptualize mental health problems in later life and negotiate the complex decisions involved with the assessment and treatment of those problems. Features new material on important topics including positive mental health, hoarding disorder, chronic pain, housing, caregiving, and ethical and legal concerns Substantially revised and updated throughout, including reference to the DSM-5 Offers chapter-end recommendations of websites for further information Includes discussion questions and critical thinking questions at the end of each chapter Aging and Mental Health, Third Edition is an ideal text for advanced undergraduate and graduate students in psychology, for service providers in psychology, psychiatry, social work, and counseling, and for clinicians who are experienced mental health service providers but who have not had much experience working specifically with older adults and their families.
Multimedia Data Processing and Computing by Suman Kumar Swarnkar,J P Patra,Tien Anh Tran,Bharat Bhushan,Santosh Biswas Pdf
This book focuses on different applications of multimedia with supervised and unsupervised data engineering in the modern world. It includes AI-based soft computing and machine techniques in the field of medical diagnosis, biometrics, networking, manufacturing, data science, automation in electronics industries, and many more relevant fields. Multimedia Data Processing and Computing provides a complete introduction to machine learning concepts, as well as practical guidance on how to use machine learning tools and techniques in real-world data engineering situations. It is divided into three sections. In this book on multimedia data engineering and machine learning, the reader will learn how to prepare inputs, interpret outputs, appraise discoveries, and employ algorithmic strategies that are at the heart of successful data mining. The chapters focus on the use of various machine learning algorithms, neural net- work algorithms, evolutionary techniques, fuzzy logic techniques, and deep learning techniques through projects, so that the reader can easily understand not only the concept of different algorithms but also the real-world implementation of the algorithms using IoT devices. The authors bring together concepts, ideas, paradigms, tools, methodologies, and strategies that span both supervised and unsupervised engineering, with a particular emphasis on multimedia data engineering. The authors also emphasize the need for developing a foundation of machine learning expertise in order to deal with a variety of real-world case studies in a variety of sectors such as biological communication systems, healthcare, security, finance, and economics, among others. Finally, the book also presents real-world case studies from machine learning ecosystems to demonstrate the necessary machine learning skills to become a successful practitioner. The primary users for the book include undergraduate and postgraduate students, researchers, academicians, specialists, and practitioners in computer science and engineering.
Persuasive Technology: Development and Implementation of Personalized Technologies to Change Attitudes and Behaviors by Peter W. de Vries,Harri Oinas-Kukkonen,Liseth Siemons,Nienke Beerlage-de Jong,Lisette van Gemert-Pijnen Pdf
This book constitutes the refereed proceedings of the 12th International Conference on Persuasive Technology, PERSUASIVE 2017, held in Amsterdam, The Netherlands, in April 2017. The 23 revised full papers presented were carefully reviewed and selected from 85 submissions. The papers are grouped in topical sections on health(care), monitoring, and coaching; personality, personalization, and persuasion; motivations, facilitators, and barriers; design principles and strategies.
Smart Healthcare Monitoring Using IoT with 5G by Meenu Gupta,Gopal Chaudhary,Victor Hugo C. de Albuquerque Pdf
Focusing on the challenges, directions, and future predictions with the role of 5G in smart healthcare monitoring, this book offers the fundamental concepts and analyses on the methods to apply Internet of Things (IoT) in monitoring devices for diagnosing and transferring data. It also discusses self-managing to help providers improve their patients' healthcare experience. Smart Healthcare Monitoring Using IoT with 5G: Challenges, Directions, and Future Predictions illustrates user-focused wearable devices such as Fitbit health monitors and smartwatches by which consumers can self-manage and self-monitor their own health. The book covers new points of security and privacy concerns, with the expectation of IoT devices gaining more popularity within the next ten years. Case studies depicting applications and best practices as well as future predictions of smart healthcare monitoring by way of a 5G network are also included. Interested readers of this book include anyone working or involved in research in the field of smart healthcare, such as healthcare specialists, computer science engineers, electronics engineers, and pharmaceutical practitioners.
Diabetes Digital Health by David C. Klonoff,David Kerr,Shelagh A. Mulvaney Pdf
Diabetes Digital Health brings together the multifaceted information surrounding the science of digital health from an academic, regulatory, industrial, investment and cybersecurity perspective. Clinicians and researchers who are developing and evaluating mobile apps for diabetes patients will find this essential reading, as will industry people whose companies are developing mobile apps and sensors. Provides valuable information for clinicians, researchers and industry about the design and evaluation of patient-facing diabetes adherence technologies Highlights cutting-edge topics that are presented and discussed at the Digital Diabetes Congress
Structural Health Monitoring by N. Rajic,W.K. Chiu,M. Veidt,A. Mita,N. Takeda Pdf
The book presents the proceedings of the 9th Asia-Pacific Workshop on Structural Health Monitoring. With the increasing worldwide emphasis on asset sustainability, there is a trend toward Condition-Based Maintenance (CBM) and Reliability-Centred Maintenance (RCM). Both approaches require diagnostic systems which detect damage and monitor structural health and/or prognostic systems that predict the future health of a structure. Keywords: Vibration Monitoring, Railway Bridge, Strain-based Damage, Turbine Blades, Crack and Temperature Sensing, Bone Degradation, Prefabricated Concrete Frame, Impact Damage in Composites, Ferroelectric Single Crystals, Evaluation of Human Injury, Automatic Damage Assessment, Metal-Composite Plates, Osseointegration, High-rise Buildings, Acoustic Emission Source. Earthquake, Wind Turbine Rotor Blades. Smart Cables, Thermal Damages, Cement Materials, Multi-parameter Monitoring, Petri Net Model, Maintenance Strategies, Load Bearing Antenna, Thin Metal Joints, Aerospace Structure.
This book introduces the field of Health Web Science and presents methods for information gathering from written social media data. It explores the availability and utility of the personal medical information shared on social media platforms and determines ways to apply this largely untapped information source to healthcare systems and public health monitoring. Introducing an innovative concept for integrating social media data with clinical data, it addresses the crucial aspect of combining experiential data from social media with clinical evidence, and explores how the variety of available social media content can be analyzed and implemented. The book tackles a range of topics including social media’s role in healthcare, the gathering of shared information, and the integration of clinical and social media data. Application examples of social media for health monitoring, along with its usage in patient treatment are also provided. The book also considers the ethical and legal issues of gathering and utilizing social media data, along with the risks and challenges that must be considered when integrating social media data into healthcare choices. With an increased interest internationally in E-Health, Health 2.0, Medicine 2.0 and the recent birth of the discipline of Web Science, this book will be a valuable resource for researchers and practitioners investigating this emerging topic.
Building Cloud Data Platforms Solutions by Anouar BEN ZAHRA Pdf
"Building Cloud Data Platforms Solutions: An End-to-End Guide for Designing, Implementing, and Managing Robust Data Solutions in the Cloud" comprehensively covers a wide range of topics related to building data platforms in the cloud. This book provides a deep exploration of the essential concepts, strategies, and best practices involved in designing, implementing, and managing end-to-end data solutions. The book begins by introducing the fundamental principles and benefits of cloud computing, with a specific focus on its impact on data management and analytics. It covers various cloud services and architectures, enabling readers to understand the foundation upon which cloud data platforms are built. Next, the book dives into key considerations for building cloud data solutions, aligning business needs with cloud data strategies, and ensuring scalability, security, and compliance. It explores the process of data ingestion, discussing various techniques for acquiring and ingesting data from different sources into the cloud platform. The book then delves into data storage and management in the cloud. It covers different storage options, such as data lakes and data warehouses, and discusses strategies for organizing and optimizing data storage to facilitate efficient data processing and analytics. It also addresses data governance, data quality, and data integration techniques to ensure data integrity and consistency across the platform. A significant portion of the book is dedicated to data processing and analytics in the cloud. It explores modern data processing frameworks and technologies, such as Apache Spark and serverless computing, and provides practical guidance on implementing scalable and efficient data processing pipelines. The book also covers advanced analytics techniques, including machine learning and AI, and demonstrates how these can be integrated into the data platform to unlock valuable insights. Furthermore, the book addresses an aspects of data platform monitoring, security, and performance optimization. It explores techniques for monitoring data pipelines, ensuring data security, and optimizing performance to meet the demands of real-time data processing and analytics. Throughout the book, real-world examples, case studies, and best practices are provided to illustrate the concepts discussed. This helps readers apply the knowledge gained to their own data platform projects.
Mobile and Wearable Systems for Health Monitoring by Mohamed Elgendi,Richard Ribon Fletcher,Derek Abbott,Dingchang Zheng,Panicos Kyriacou,Carlo Menon Pdf
Nursing Informatics 2016 by W. Sermeus,P.M. Procter,P. Weber Pdf
As the importance of electronic and digital devices in the provision of healthcare increases, so does the need for interdisciplinary collaboration to make the most of the new technical possibilities which have become available. This book presents the proceedings of the 13th International Conference on Nursing Informatics, held in Geneva, Switzerland, in June 2016. This biennial international conference provides one of the most important opportunities for healthcare professionals from around the world to gather and exchange expertise in the research and practice of both basic and applied nursing informatics. The theme of this 13th conference is eHealth for All: Every Level Collaboration – From Project to Realization. The book includes all full papers, as well as workshops, panels and poster summaries from the conference. Subjects covered include a wide range of topics, from robotic assistance in managing medication to intelligent wardrobes, and from low-cost wearables for fatigue and back stress management to big data analytics for optimizing work processes, and the book will be of interest to all those working in the design and provision of healthcare today.
Data Labeling in Machine Learning with Python by Vijaya Kumar Suda Pdf
Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.
Prevention Practice in Primary Care by Sherri Sheinfeld Gorin Pdf
Amid the ongoing changes in how health care is administered and financed, prevention-oriented care is a critical and cost-effective method for improving population health through primary care. As the key figure in promoting patients' health and prevention of disease, the primary care provider can play a major role in patient engagement, self-management, and behavior change. Prevention Practice in Primary Care systematically explores state-of-the-art practical approaches to effective prevention in primary care. Guided by theory and evidence, the book reviews approaches to risk factor identification and modification for the major causes of mortality in adulthood, including cancer, stroke, and cardiovascular disease. Topical coverage in this book includes: · the practical applications of genomics and proteomics to personalizing prevention · transformative approaches to practice change, including the patient-centered medical home, academic detailing, and practice facilitation · Engaging self-management and behavior change using counseling tools (goal setting, assessing the stage of change, motivational interviewing, and the five A's) Prevention Practice in Primary Care is a vital, practical guidebook for the implementation of evidence-based prevention to improve patient health. Brief, simple summaries and innovative content make it book a valuable reference for busy practitioners and students alike.
PHealth 2015 by B. Blobel,M. Lindén,M.U. Ahmed Pdf
Smart mobile systems, smart textiles, smart implants and sensor controlled medical devices are among the recent developments which have become important enablers for telemedicine and next-generation health services. Social media and gamification have added yet another dimension to Personalized Health (pHealth). This book presents the proceedings of pHealth 2015, the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health, held in Västerås, Sweden, in June 2015. The conference addressed mobile technologies, knowledge-driven applications and computer-assisted decision support, as well as apps designed to support the elderly and those with chronic conditions in their daily lives. The 23 conference papers, three keynotes and two specially invited contributions included here address the fundamental scientific and methodological challenges of adaptive, autonomous and intelligent pHealth approaches. Participants at this truly interdisciplinary conference included representatives from all relevant stakeholder communities, and the topics covered will be of interest to all those whose work involves improving the quality of medical services, optimizing industrial competitiveness and managing healthcare costs.