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Cancer Informatics chronicles the development of the National Cancer Institute's new Cancer Informatics Infrastructure (CII) - an information management system infrastructure designed to faciliate clinical trials, provide for reliable, secure information exchange, and improve patient care. The book details the challenges involved in creating and managing such a knowledge base, including technologies, standards, and current, state-of-the-art applications. The ultimate goal of CII is to function as an enabler of clinical trials, expediting the clinical trials lifecycle, faciliating faster and safer drug development and more appropriate treatment choices for cancer patients. Contributors address the role the CII must play in converting the growing knowledge of genes, proteins, and pathways into appropriate preventative, diagnostic, and therapeutic measures. Presented in four sections, the first provides an overview of the processes involved in moving the infrastructure for cancer from theory into practice. Sections two through four offer the latest work done in the areas of technology, cancer-specific and national standards, and applications to faciliate clinical trials.
Oncology Informatics: Using Health Information Technology to Improve Processes and Outcomes in Cancer Care encapsulates National Cancer Institute-collected evidence into a format that is optimally useful for hospital planners, physicians, researcher, and informaticians alike as they collectively strive to accelerate progress against cancer using informatics tools. This book is a formational guide for turning clinical systems into engines of discovery as well as a translational guide for moving evidence into practice. It meets recommendations from the National Academies of Science to "reorient the research portfolio" toward providing greater "cognitive support for physicians, patients, and their caregivers" to "improve patient outcomes." Data from systems studies have suggested that oncology and primary care systems are prone to errors of omission, which can lead to fatal consequences downstream. By infusing the best science across disciplines, this book creates new environments of "Smart and Connected Health." Oncology Informatics is also a policy guide in an era of extensive reform in healthcare settings, including new incentives for healthcare providers to demonstrate "meaningful use" of these technologies to improve system safety, engage patients, ensure continuity of care, enable population health, and protect privacy. Oncology Informatics acknowledges this extraordinary turn of events and offers practical guidance for meeting meaningful use requirements in the service of improved cancer care. Anyone who wishes to take full advantage of the health information revolution in oncology to accelerate successes against cancer will find the information in this book valuable. Presents a pragmatic perspective for practitioners and allied health care professionals on how to implement Health I.T. solutions in a way that will minimize disruption while optimizing practice goals Proposes evidence-based guidelines for designers on how to create system interfaces that are easy to use, efficacious, and timesaving Offers insight for researchers into the ways in which informatics tools in oncology can be utilized to shorten the distance between discovery and practice
Cancer Informatics in Post-Genomic Era provides both the necessary methodology and practical information tools for analyzing data in the field of medical information science. This, of course, requires analytic tools. Those tools are garnered by developing and assessing methods and systems for the acquisition, processing, and interpretation of patient data, aided by scientific discovery. Key challenges in this field include integrating research and clinical care, sharing data, and establishing partnerships within and across sectors of patient diagnosis and treatment.
This book adopts an integrated and workflow-based treatment of the field of personalized and precision medicine (PPM). Outlined within are established, proven and mature workflows as well as emerging and highly-promising opportunities for development. Each workflow is reviewed in terms of its operation and how they are enabled by a multitude of informatics methods and infrastructures. The book goes on to describe which parts are crucial to discovery and which are essential to delivery and how each of these interface and feed into one-another. Personalized and Precision Medicine Informatics provides a comprehensive review of the integrative as well as interpretive nature of the topic and brings together a large body of literature to define the topic and ensure that this is the key reference for the topic. It is an unique contribution that is positioned to be an essential guide for both PPM experts and non-experts, and for both informatics and non-informatics professionals.
Reflecting the increased importance of the collaborations between radiation oncology and informatics professionals, Informatics in Radiation Oncology discusses the benefits of applying informatics principles to the processes within radiotherapy. It explores how treatment and imaging information is represented, stored, and retrieved as well as how this information relates to other patient data. The book deepens your knowledge of current and emerging information technology and informatics principles applied to radiation oncology so that all the data gathered—from laboratory results to medical images—can be fully exploited to make treatments more effective and processes more efficient. After introducing the basics of informatics and its connection to radiation oncology, the book examines the process of healthcare delivery in radiation oncology, the challenges of managing images in radiotherapy, and the burgeoning field of radiogenomics. It then presents teaching, clinical trials, and research tools and describes open access clinical imaging archives in radiotherapy, techniques for maximizing information from multimodality imaging, and the roles of images in treatment planning. It also looks at how informatics can improve treatment planning, the safety and efficiency of delivery systems, image-guided patient positioning, and patient assessment. The book concludes with discussions on how outcomes modeling evaluates the effectiveness of treatments, how quality control informatics improves the reliability of processes, and how to perform quality assurance on the informatics tools. With contributions from a host of top international experts in radiation oncology, medical physics, and informatics, this book leads the way in moving the field forward. It encourages you to find new ways of applying informatics to radiation oncology and help your patients in their fight against cancer.
This volume covers a wide variety of state of the art cancer-related methods and tools for data analysis and interpretation. Chapters were designed to attract a broad readership, ranging from active researchers in computational biology and bioinformatics developers, clinical oncologists, and anti-cancer drug developers wishing to rationalize their search for new compounds. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, installation instructions for computational tools discussed, explanations of the input and output formats, and illustrative examples of applications. Authoritative and cutting-edge, Cancer Bioinformatics: Methods and Protocols aims to support researchers performing computational analysis of cancer-related data.
This unique collection synthesizes insights and evidence from innovators in consumer informatics and highlights the technical, behavioral, social, and policy issues driving digital health today and in the foreseeable future. Consumer Informatics and Digital Health presents the fundamentals of mobile health, reviews the evidence for consumer technology as a driver of health behavior change, and examines user experience and real-world technology design challenges and successes. Additionally, it identifies key considerations for successfully engaging consumers in their own care, considers the ethics of using personal health information in research, and outlines implications for health system redesign. The editors’ integrative systems approach heralds a future of technological advances tempered by best practices drawn from today’s critical policy goals of patient engagement, community health promotion, and health equity. Here’s the inside view of consumer health informatics and key digital fields that students and professionals will find inspiring, informative, and thought-provoking. Included among the topics: • Healthcare social media for consumer informatics • Understanding usability, accessibility, and human-centered design principles • Understanding the fundamentals of design for motivation and behavior change • Digital tools for parents: innovations in pediatric urgent care • Behavioral medicine and informatics in the cancer community • Content strategy: writing for health consumers on the web • Open science and the future of data analytics • Digital approaches to engage consumers in value-based purchasing Consumer Informatics and Digital Health takes an expansive view of the fields influencing consumer informatics and offers practical case-based guidance for a broad range of audiences, including students, educators, researchers, journalists, and policymakers interested in biomedical informatics, mobile health, information science, and population health. It has as much to offer readers in clinical fields such as medicine, nursing, and psychology as it does to those engaged in digital pursuits.
This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.
This book introduces readers to essential methods and applications in translational biomedical informatics, which include biomedical big data, cloud computing and algorithms for understanding omics data, imaging data, electronic health records and public health data. The storage, retrieval, mining and knowledge discovery of biomedical big data will be among the key challenges for future translational research. The paradigm for precision medicine and healthcare needs to integratively analyze not only the data at the same level – e.g. different omics data at the molecular level – but also data from different levels – the molecular, cellular, tissue, clinical and public health level. This book discusses the following major aspects: the structure of cross-level data; clinical patient information and its shareability; and standardization and privacy. It offers a valuable guide for all biologists, biomedical informaticians and clinicians with an interest in Precision Medicine Informatics.