This open access book explores how expertise about bipolar disorder is performed on American and French digital platforms by combining insights from STS, medical sociology and media studies. It addresses topical questions, including: How do different stakeholders engage with online technologies to perform expertise about bipolar disorder? How does the use of the internet for processes of knowledge evaluation and production allow for people diagnosed with bipolar disorder to reposition themselves in relation to medical professionals? How do cultural markers shape the online performance of expertise about bipolar disorder? And what individualizing or collectivity-generating effects does the internet have in relation to the performance of expertise? The book constitutes a critical and nuanced intervention into dominant discourses which approach the internet either as a quick technological fix or as a postmodern version of Pandora's box, sowing distrust among people and threatening unified conceptualizations and organized forms of knowledge.

Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine.

About the editors:

Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics.

Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics."

The areas we deal with in biochemical engineering have expanded to include many various organisms and humans. This book has gathered together the information of these expanded areas in biochemical engineering in Japan. These two volumes are composed of 15 chapters on microbial cultivation techniques, metabolic engineering, recombinant protein production by transgenic avian cells to biomedical engineering including tissue engineering and cancer therapy. Hopefully, these volumes will give readers a glimpse of the past and also a view of what may happen in biochemical engineering in Japan.

Low Power Analog CMOS for Cardiac Pacemakers proposes new techniques for the reduction of power consumption in analog integrated circuits. Our main example is the pacemaker sense channel, which is representative of a broader class of biomedical circuits aimed at qualitatively detecting biological signals.
The first and second chapters are a tutorial presentation on implantable medical devices and pacemakers from the circuit designer point of view. This is illustrated by the requirements and solutions applied in our implementation of an industrial IC for pacemakers. There from, the book discusses the means for reduction of power consumption at three levels: base technology, power-oriented analytical synthesis procedures and circuit architecture.

Pervasive healthcare is the conceptual system of providing healthcare to anyone, at anytime, and anywhere by removing restraints of time and location while increasing both the coverage and the quality of healthcare. Pervasive Healthcare Monitoring is at the forefront of this research, and presents the ways in which mobile and wireless technologies can be used to implement the vision of pervasive healthcare.

This vision includes prevention, healthcare maintenance and checkups; short-term monitoring (home healthcare monitoring), long-term monitoring (nursing home), and personalized healthcare monitoring; and incidence detection and management, emergency intervention, and transportation and treatment. The pervasive healthcare applications include pervasive health monitoring, intelligent emergency management system, pervasive healthcare data access, and ubiquitous mobile telemedicine.

Pervasive Healthcare Monitoring fills the need for a research-oriented book on the wide array of emerging healthcare applications and services, including the treatment of several new wireless technologies and the ways in which they will implement the vision of pervasive healthcare. This book is written primarily for university faculty and graduate students in the field of healthcare technologies, and industry professionals involved in healthcare IT research, design, and development.

Health Information Exchange: Navigating and Managing a Network of Health Information Systems, Second Edition, now fully updated, is a practical guide on how to understand, manage and make use of a health information exchange infrastructure, which moves patient-centered information within the health care system. The book informs and guides the development of new infrastructures as well as the management of existing and expanding infrastructures across the globe. Sections explore the reasons for the health information exchange (HIE) infrastructures, how to manage them, examines the key drivers of HIE, and barriers to their widespread use. In addition, the book explains the underlying technologies and methods for conducting HIE across communities as well as nations. Finally, the book explains the principles of governing an organization that chiefly moves protected health information around. The text unravels the complexities of HIE and provides guidance for those who need to access HIE data and support operations.

The interaction of tissue and synthetic material can be the pivotal element in the artificial replacement of a body part damaged by disease or trauma. Hip replacements, dental implants, pacemaker leads, vascular grafts, heart valves, and dialysis machines all involve microscopic, tissue-level events that determine the success or failure of such devices. An Introduction to Tissue-Biomaterial Interactions acquaints an undergraduate audience with the fundamental biological processes that influence these sophisticated, cutting-edge procedures.

Chapters one through three provide more detail about the molecular-level events that happen at the tissue-implant interface, while chapters four through ten explore selected material, biological, and physiological consequences of these events. The importance of the body’s wound-healing response is emphasized throughout. Specific topics covered include:

• Structure and properties of biomaterials
• Proteins
• Protein-surface interactions
• Blood-biomaterial interactions
• Inflammation and infection
• The immune system
• Biomaterial responses to implantation
• Biomaterial surface engineering
• Intimal hyperplasia and osseointegration as examples of tissue-biomaterial interactions

The text also provides extensive coverage of the three pertinent interfaces between the body and the biomaterial, between the body and the living cells, and between the cells and the biomaterial that are critical in the development of tissue-engineered products that incorporate living cells within a biomaterial matrix.

Ideal for a one-semester, biomedical engineering course, An Introduction to Tissue-Biomaterial Interactions provides a solid framework for understanding today’s and tomorrow’s implantable biomedical devices.

This book focuses on biomaterials of different forms used for medical implants. The authors introduce the characteristics and properties of biomaterials and then dedicate special chapters to metallic, ceramic, polymeric and composite biomaterials. Case studies on sterilization methods by biomaterials are also presented. Finally, the authors describe the degradation and effects of biomaterials in living tissue.

Next-Generation Sequencing (NGS) is increasingly common and has applications in various fields such as clinical diagnosis, animal and plant breeding, and conservation of species. This incredible tool has become cost-effective. However, it generates a deluge of sequence data that requires efficient analysis. The highly sought-after skills in computational and statistical analyses include machine learning and, are essential for successful research within a wide range of specializations, such as identifying causes of cancer, vaccine design, new antibiotics, drug development, personalized medicine, and increased crop yields in agriculture.This invaluable book provides step-by-step guides to complex topics that make it easy for readers to perform specific analyses, from raw sequenced data to answer important biological questions using machine learning methods. It is an excellent hands-on material for lecturers who conduct courses in bioinformatics and as reference material for professionals. The chapters are standalone recipes making them suitable for readers who wish to self-learn selected topics. Readers gain the essential skills necessary to work on sequenced data from NGS platforms; hence, making themselves more attractive to employers who need skilled bioinformaticians.

Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis.

This book highlights the latest advances on the implementation and adaptation of blockchain technologies in real-world scientific, biomedical, and data applications. It presents rapid advancements in life sciences research and development by applying the unique capabilities inherent in distributed ledger technologies. The book unveils the current uses of blockchain in drug discovery, drug and device tracking, real-world data collection, and increased patient engagement used to unlock opportunities to advance life sciences research. This paradigm shift is explored from the perspectives of pharmaceutical professionals, biotechnology start-ups, regulatory agencies, ethical review boards, and blockchain developers. This book enlightens readers about the opportunities to empower and enable data in life sciences.

Many aspects of modern life have become personalized, yet healthcare practices have been lagging behind in this trend. It is now becoming more common to use big data analysis to improve current healthcare and medicinal systems, and offer better health services to all citizens. Applying Big Data Analytics in Bioinformatics and Medicine is a comprehensive reference source that overviews the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Featuring coverage on relevant topics that include smart data, proteomics, medical data storage, and drug design, this publication is an ideal resource for medical professionals, healthcare practitioners, academicians, and researchers interested in the latest trends and techniques in personalized medicine.

One of the first applications of ultrasound was in submarine sonar equip ment. Since then ultrasound has found increasing applications, particularly in industry, but increasingly in biomedicine. For many years ultrasound has been used in physical therapy, although only in the past decade or two has it evolved from laboratory curiosity to a well-established diagnostic imaging modality. Ultrasound is now a widely accepted, indeed pervasive, diagnos tic and therapeutic tool in the medical field, and its applications are increasing rapidly. Our intent in developing this book is to provide a coherent tutorial intro duction to the field of medical ultrasound at a level suitable for those en tering the area from either medical or scientific backgrounds. The topics discussed should be of interest to nearly all medical and health care per sonnel needing to understand or operate ultrasonic devices, including clini cians, medical technicians, physiotherapists, medical physicists, and other biomedical scientists interested in the field. The book opens with a description of the basic principles of propagating acoustic waves, explains how they interact with a wide range of biological systems, and outlines the effects they produce. To provide practical infor mation to operators of ultrasound equipment, we have included thorough coverage of the details of ultrasonic instrumentation and measurement techniques, and set forth the framework for an effective quality assurance program."

The purpose of the Mental Health Practice in a Digital World: A Clinicians Guide book is to prepare clinicians to understand, critically evaluate, and embrace well-designed and validated technologies that have the potential of transforming the access, affordability, and accountability of mental healthcare. The reader will become aware of the practical applications of technology in mental health as well as research supporting information technology tools, policy debates. Each chapter contains either examples or scenarios that are relevant to the current practice of mental health care. Policy makers, application developers, scientists, and executives that have lead or supported the use of technologies in real world practice are chapter authors. The goal for this book is to be the key resource for current and future mental health clinicians in the U.S. and around the world to become familiar with technology innovations and how they impact and improve clinical practice.

Virtual Reality has the potential to provide descriptive and practical information for medical training and therapy while relieving the patient or the physician. Multimodal interactions between the user and the virtual environment facilitate the generation of high-fidelity sensory impressions, by using not only visual and auditory, but also kinesthetic, tactile, and even olfactory feedback modalities. On the basis of the existing physiological constraints, Virtual Reality in Medicine derives the technical requirements and design principles of multimodal input devices, displays, and rendering techniques. Resulting from a course taught by the authors, Virtual Reality in Medicine presents examples for surgical training, intra-operative augmentation, and rehabilitation that are already in use as well as those currently in development. It is well suited as introductory material for engineering and computer science students, as well as researchers who want to learn more about basic technologies in the area of virtual reality applied to medicine. It also provides a broad overview to non-engineering students as well as clinical users, who desire to learn more about the current state of the art and future applications of this technology.

Over the last twenty years integrated care has been touted as a solution to many issues in health services, such as insufficient coordination between services, cumbersome organizational boundaries, interrupted patient journeys, as well as spiraling health care costs. However, despite volumes of research, the field has seen few innovative advances in recent years. In particular, prevailing integrated care implementation practice and research appear to be very health science centred, spurning approaches from other disciplines. Axel Kaehne argues that it is time to re-evaluate how we investigate care integration. He asks us to radically question our assumptions about integrated care as a managerial, organisational and behavioural endeavor. This is a profound departure from conventional thinking about integration in health and social care. Kaehne reveals the tacit assumptions we make when we manage and change health services and offers a fresh perspective on care integration whilst inviting readers to examine long established research orthodoxies. This eclectic conceptual and theoretical approach produces surprising insights for everyone who is ready to see things anew.

This book provides an interdisciplinary look at emerging trends in signal processing and biomedicine found at the intersection of healthcare, engineering, and computer science. It examines the vital role signal processing plays in enabling a new generation of technology based on big data, and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include analysis of medical images, machine learning, biomedical nanosensors, wireless technologies, and instrumentation and electrical stimulation. Biomedical Signal Processing: Innovation and Applications presents tutorials and examples of successful applications, and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology.

This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin. In the first chapter following the Introduction to this book, we review three prediction approaches of respiratory motion: model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the following chapter, we present a phantom study-prediction of human motion with distributed body sensors-using a Polhemus Liberty AC magnetic tracker. Next we describe respiratory motion estimation with hybrid implementation of extended Kalman filter. The given method assigns the recurrent neural network the role of the predictor and the extended Kalman filter the role of the corrector. After that, we present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction, we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. We have evaluated the new algorithm by comparing the prediction overshoot and the tracking estimation value. The experimental results of 448 patients' breathing patterns validated the proposed irregular breathing classifier in the last chapter.

The original role of RP was to confirm the shape and feel of concept design, but innovations in RP now allow for the development of sophisticated medical devices such as catheters, stents, drug delivery systems, syringes and cardio-vascular devices, and more. RP has moved beyond medical devices, as surgeons now regularly use RP models to brainstorm strategies for surgeries. This book presents new uses for rapid prototyping in state-of-the-art medical applications.

This book provides a practically applicable guide to designing evidence-based medical apps and mHealth interventions. It features detailed guidance and case studies where applicable on the best practices and available techniques from both technological (platform technologies, toolkits, sensors) and research perspectives. This approach enables the reader to develop a deep understanding of how to collect the appropriate data and work with users to build a user friendly app for their target audience. Information on how researchers and designers can communicate their intentions with a variety of stakeholders including medical practitioners, developers and researchers to ensure the best possible decisions are made during the development process to produce an app of optimal quality that also considers usability. Developing Medical Apps and mHealth Interventions comprehensively covers the development of medical and health apps for researchers, informaticians and physicians, and is a valuable resource for the experienced professional and trainee seeking a text on how to develop user friendly medical apps.