This book explores the latest and most relevant topics in the field of computational bioengineering and bioinformatics, with a particular focus on patient-specific, disease-progression modeling. It covers computational methods for cardiovascular disease prediction, with an emphasis on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for disease characterization, and recent advances in areas such as biomechanics, cardiovascular engineering, patient-specific modeling, population-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and dental biomechanics, tissue and cell engineering, computational chemistry and high-performance computing. As such, it is a valuable resource for researchers, medical and bioengineering students, and medical device and software experts

Computational Modeling in Bioengineering and Bioinformatics promotes complementary disciplines that hold great promise for the advancement of research and development in complex medical and biological systems, and in the environment, public health, drug design, and so on. It provides a common platform by bridging these two very important and complementary disciplines into an interactive and attractive forum. Chapters cover biomechanics and bioimaging, biomedical decision support system, data mining, personalized diagnoses, bio-signal processing, protein structure prediction, tissue and cell engineering, biomedical image processing, analysis and visualization, high performance computing and sports bioengineering. The book's chapters are the result of many international projects in the area of bioengineering and bioinformatics done at the Research and Development Center for Bioengineering BioIRC and by the Faculty of Engineering at the University of Kragujevac, Serbia. - Presents recent advances at the crossroads of biomedical engineering and bioinformatics, one of the hottest areas in biomedical and clinical research - Discusses a wide range of leading-edge research topics, including biomechanics and bioimaging, biomedical decision support systems, data mining, personalized diagnoses, bio-signal processing, protein structure prediction, tissue and cell engineering, amongst others - Includes coverage of biomechanical, bioengineering and computational methods of treatment and diagnosis

Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. - Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems - Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems - Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data

Issues in Bioengineering and Bioinformatics: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Lifetime Data Analysis. The editors have built Issues in Bioengineering and Bioinformatics: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Lifetime Data Analysis in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Bioengineering and Bioinformatics: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Technological tools and computational techniques have enhanced the healthcare industry. These advancements have led to significant progress and novel opportunities for biomedical engineering. Biomedical Engineering: Concepts, Methodologies, Tools, and Applications is an authoritative reference source for emerging scholarly research on trends, techniques, and future directions in the field of biomedical engineering technologies. Highlighting a comprehensive range of topics such as nanotechnology, biomaterials, and robotics, this multi-volume book is ideally designed for medical practitioners, professionals, students, engineers, and researchers interested in the latest developments in biomedical technology.

This book gathers 30 papers presented at the 21st PCBBE, which was hosted by the University of Zielona Góra, Poland, and offered a valuable forum for exchanging ideas and presenting the latest developments in all areas of biomedical engineering. Biocybernetics and biomedical engineering are currently considered one of the most promising ways to improve health care and, consequently, the quality of life. Innovative technical solutions can better meet physicians’ needs and stimulate the development of medical diagnostics and therapy. We are currently witnessing a profound change in the role of medicine, which is becoming ubiquitous in everyday life thanks to technological advances. Further, the development of civilization manifests itself in efforts to unlock the secrets of the human body, and to mimic biological systems in engineering. The biannual Polish Conference on Biocybernetics and Biomedical Engineering (PCBBE) has been held for nearly four decades and has attracted scientists and professionals in the fields of engineering, medicine, physics, and computer science. Gathering the outcomes of this conference, the book introduces the reader to recent developments and achievements in biocybernetics and biomedical engineering.

Repetitive structures in biological sequences are emerging as an active focus of research and the unifying concept of "repeatome" (the ensemble of knowledge associated with repeating structures in genomic/proteomic sequences) has been recently proposed in order to highlight several converging trends. One main trend is the ongoing discovery that genomic repetitions are linked to many biological significant events and functions. Diseases (e.g. Huntington's disease) have been causally linked with abnormal expansion of certain repeating sequences in the human genome. Deletions or multiple copy duplications of genes (Copy Number Variations) are important in the aetiology of cancer, Alzheimer, and Parkinson diseases. A second converging trend has been the emergence of many different models and algorithms for detecting non-obvious repeating patterns in strings with applications to in genomic data. Borrowing methodologies from combinatorial pattern, matching, string algorithms, data structures, data mining and machine learning these new approaches break the limitations of the current approaches and offer a new way to design better trans-disciplinary research. The articles collected in this book provides a glance into the rich emerging area of repeatome research, addressing some of its pressing challenges. We believe that these contributions are valuable resources for repeatome research and will stimulate further research from bioinformatic, statistical, and biological points of view.