The papers in this volume address the state-of-the-art and future directions in applied mathematics in both scattering theory and biomedical technology. A workshop held in Metsovo, Greece during the summer of 1997 brought together some of the world's foremose experts in the field with researchers working in Greece. Sixteen of the contributed papers appear in this volume. All the papers give new directions, and in several cases, the most important scientific contributions in the fields.
Medical Data Sharing, Harmonization and Analytics serves as the basis for understanding the rapidly evolving field of medical data harmonization combined with the latest cloud infrastructures for storing the harmonized (shared) data. Chapters cover the latest research and applications on data sharing and protection in the medical domain, cohort integration through the recent advancements in data harmonization, cloud computing for storing and securing the patient data, and data analytics for effectively processing the harmonized data. - Examines the unmet needs in chronic diseases as a part of medical data sharing - Discusses ethical, legal and privacy issues as part of data protection - Combines data harmonization and big data analytics strategies in shared medical data, along with relevant case studies in chronic diseases
Atherosclerotic Plaque Characterization Methods Based on Coronary Imaging provides a complete review of computer methods for atherosclerotic plaque reconstruction and characterization. The authors, with their expertise from biomedical engineering, computer science, and cardiology, offer a holistic view. The focus of the book is on the presentation of major imaging techniques, including their limitations. It includes details on the mechanical characterization and properties of plaques and appropriate constitutive models to describe the mechanical behavior of plaques. The authors explore the challenges of using multiple coronary imaging technologies, and provide the pros and cons of invasive vs. non-invasive techniques. Methods for plaque characterization and 3D reconstruction of coronary arteries using IVUS, OCT, and CT images are described. This book will help readers study new trends in image processing analysis and plaque characterization, implement automated plaque characterization methodologies, understand coronary imaging drawbacks, and comprehend 3 dimensional coronary artery and plaque reconstruction methods. - Describes the multimodality imaging techniques that are commonly used in the diagnosis of arterial diseases, including intravascular ultrasound, optical coherence tomography, angiography, computed tomography angiography, and magnetic resonance angiography - Discusses in-depth the computational methods which can be used for the detection of different plaque types - Explores plaque in 3D reconstruction methods and plaque modeling approaches
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 volume addresses the state-of-the-art and future directions of informatics. Several senior researchers and graduate students present their research and work here. The purpose of the book is to disseminate the latest scientific, engineering and technical information in various fields of informatics. It covers a wide range of subjects, from theoretical computer science, software engineering, systems and scientific computing to networking and applied research. The book can be used either as a reference for related scientific work or as educational material for advanced computer science courses.
Multiscale Modelling in Biomedical Engineering Discover how multiscale modeling can enhance patient treatment and outcomes In Multiscale Modelling in Biomedical Engineering, an accomplished team of biomedical professionals delivers a robust treatment of the foundation and background of a general computational methodology for multi-scale modeling. The authors demonstrate how this methodology can be applied to various fields of biomedicine, with a particular focus on orthopedics and cardiovascular medicine. The book begins with a description of the relationship between multiscale modeling and systems biology before moving on to proceed systematically upwards in hierarchical levels from the molecular to the cellular, tissue, and organ level. It then examines multiscale modeling applications in specific functional areas, like mechanotransduction, musculoskeletal, and cardiovascular systems. Multiscale Modelling in Biomedical Engineering offers readers experiments and exercises to illustrate and implement the concepts contained within. Readers will also benefit from the inclusion of: A thorough introduction to systems biology and multi-scale modeling, including a survey of various multi-scale methods and approaches and analyses of their application in systems biology Comprehensive explorations of biomedical imaging and nanoscale modeling at the molecular, cell, tissue, and organ levels Practical discussions of the mechanotransduction perspective, including recent progress and likely future challenges In-depth examinations of risk prediction in patients using big data analytics and data mining Perfect for undergraduate and graduate students of bioengineering, biomechanics, biomedical engineering, and medicine, Multiscale Modelling in Biomedical Engineering will also earn a place in the libraries of industry professional and researchers seeking a one-stop reference to the basic engineering principles of biological systems.
Medical Data Sharing, Harmonization and Analytics serves as the basis for understanding the rapidly evolving field of medical data harmonization combined with the latest cloud infrastructures for storing the harmonized (shared) data. Chapters cover the latest research and applications on data sharing and protection in the medical domain, cohort integration through the recent advancements in data harmonization, cloud computing for storing and securing the patient data, and data analytics for effectively processing the harmonized data. - Examines the unmet needs in chronic diseases as a part of medical data sharing - Discusses ethical, legal and privacy issues as part of data protection - Combines data harmonization and big data analytics strategies in shared medical data, along with relevant case studies in chronic diseases
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