Motivated by the explosion of molecular data on humans-particularly data associated with individual patients-and the sense that there are large, as-yet-untapped opportunities to use this data to improve health outcomes, Toward Precision Medicine explores the feasibility and need for "a new taxonomy of human disease based on molecular biology" and develops a potential framework for creating one. The book says that a new data network that integrates emerging research on the molecular makeup of diseases with clinical data on individual patients could drive the development of a more accurate classification of diseases and ultimately enhance diagnosis and treatment. The "new taxonomy" that emerges would define diseases by their underlying molecular causes and other factors in addition to their traditional physical signs and symptoms. The book adds that the new data network could also improve biomedical research by enabling scientists to access patients' information during treatment while still protecting their rights. This would allow the marriage of molecular research and clinical data at the point of care, as opposed to research information continuing to reside primarily in academia. Toward Precision Medicine notes that moving toward individualized medicine requires that researchers and health care providers have access to very large sets of health- and disease-related data linked to individual patients. These data are also critical for developing the information commons, the knowledge network of disease, and ultimately the new taxonomy.

Progress and Challenges in Precision Medicine presents an insightful overview to the myriad factors of personalized and precision medicine. The availability of the human genome, large amounts of data on individual genetic variations, environmental interactions, influence of lifestyle, and cutting-edge tools and technologies for big-data analysis have led to the age of personalized and precision medicine. Bringing together a global range of experts on precision medicine, this book collects previously scattered information into one concise volume which covers the most important developments so far in precision medicine and also suggests the most likely avenues for future development. The book includes clinical information, informatics, public policy implications, and information on case studies. It is a useful reference and background work for students, researchers, and clinicians working in the biomedical and medical fields, as well as policymakers in the health sciences. - Provides an overview of the growing field of precision medicine - Contains chapters from geographically diverse experts in their field - Explores important aspects of precision medicine, including applications, ethics, and development

Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from simple autoregressive models of the CGM time series to multivariate nonlinear regression techniques of machine learning. Developments in the field have been analyzed with respect to: (i) feature set (univariate or multivariate), (ii) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling properties. In addition, simulation models of meal-derived glucose absorption and insulin dynamics and kinetics are covered, as an integral part of glucose predictive models. This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and non-stationary conditions; ensure the scalability of the optimization algorithm (learning mechanism) with respect to the size of the dataset, provided that multiple days of patient monitoring are needed to obtain a reliable predictive model; select a features set which efficiently represents both spatial and temporal dependencies between the input variables and the glucose concentration; select simulation models of subcutaneous insulin absorption and meal absorption; identify an appropriate validation procedure, and identify realistic performance measures. Describes fundamentals of modeling techniques as applied to glucose control Covers model selection process and model validation Offers computer code on a companion website to show implementation of models and algorithms Features the latest developments in the field of diabetes predictive modeling

This book is intended to provide up-to-date and emerging information in the field of diabetes mellitus with a focus on preventive, predictive and personalized medicine.

This contributed book is based on more than 20 years of researches on patient individuality, care and services of the continuously changing healthcare system. It describes how research results can be used to respond to challenges on individuality in healthcare systems. Service users’, patients’ or clients’ point of views on care and health services are urgently needed. This book describes the conceptualisation of the individualized nursing care phenomenon and the process development of the measuring instruments of that phenomenon in different contexts. It describes results from a variety of clinical contexts about individualized nursing care and explains factors associated with the perceptions and delivery of individualized nursing care from different point of views. This book may appeal to clinicians, nurses practitioners and researchers from many fields.

Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. - Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions - Provides background, milestone and examples of precision medicine - Outlines the paradigm shift towards precision medicine driven by value-based systems - Discusses future applications of precision medicine research using AI - Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine

Precision Medicine: Tools and Quantitative Approaches discusses precision and personalized medicine, two relevant topics that are revolutionizing diagnostics and treatment, while also providing a shift toward prevention. The book covers the most relevant features and explanations underlying developments in the field. A timely review on prerequisites, causes and consequences is given. Unique to this book is a combined view on technical and data analysis aspects that is mandatory for obtaining and interpreting results. This book is a valuable source for researchers in medical and life sciences, physicians and students with an interest in this emerging field of precision medicine. - Provides technological aspects in precision medicine with aspects of modern statistical and bioinformatics models and methods - Brings timely reviews on status and chances in precision medicine and associated aspects of data analysis, statistics and data interpretation - Encompasses easy access to relevant approaches, interactions and original literature

This new edition offers a state-of-the-art and integrative vision of pharmacogenomics by exploring new concepts and practical methodologies focusing on disease treatments, from cancers to cardiovascular and neurodegenerative disorders and more. The collection of these theoretical and experimental approaches facilitates problem-solving by tackling the complexity of personalized drug discovery and development. Written by leading experts in their fields for the highly successful Methods in Molecular Biology series, the book aims to provide across-the-board resources to support the translation of pharmacogenomics into better individualized health care. Authoritative and up-to-date, Pharmacogenomics in Drug Discovery and Development, Third Edition aims to aid researchers in approaching the challenges in pharmacogenomics and personalized medicine with the introduction of these novel ideas and cutting-edge methodologies.

Genomic and Precision Medicine: Primary Care, Third Edition is an invaluable resource on the state-of-the-art tools, technologies and policy issues that are required to fully realize personalized health care in the area of primary care. One of the major areas where genomic and personalized medicine is most active is the realm of the primary care practitioner. Risk, family history, personal genomics and pharmacogenomics are becoming increasingly important to the PCP and their patients, and this book discusses the implications as they relate to primary care practitioners. - Presents a comprehensive volume for primary care providers - Provides succinct commentary and key learning points that will assist providers with their local needs for the implementation of genomic and personalized medicine - Includes a current overview on major opportunities for genomic and personalized medicine in practice - Highlights case studies that illustrate the practical use of genomics in the management in patients

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