Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Cardiovascular diseases have a major impact in Western countries. Mathematical models and numerical simulations can help the understanding of physiological and pathological processes, complementing the information provided to medical doctors by medical imaging and other non-invasive means, and opening the possibility of a better diagnosis and more in-depth surgical planning.This book offers a mathematically sound and up-to-date foundation to the training of researchers, and serves as a useful reference for the development of mathematical models and numerical simulation codes. It is structured into different chapters, written by recognized experts in the field, and however it features a common thread, with consistency of notation and expressions and systematic cross-referencing. Many fundamental issues are faced, such as: the mathematical representation of vascular geometries extracted from medical images, modelling blood rheology and the complex multilayer structure of the vascular tissue, and its possible pathologies, the mechanical and chemical interaction between blood and vascular walls; the different scales coupling local and systemic dynamics. All of these topics introduce challenging mathematical and numerical problems, demanding for advanced analysis and simulation techniques. This book is addressed to graduate students and researchers in the field of bioengineering, applied mathematics and medicine, wishing to engage themselves in the fascinating task of modeling how the cardiovascular system works.

Mathematics. --- Applications of Mathematics. --- Cardiology. --- Mathematical Biology in General. --- Physiological, Cellular and Medical Topics. --- Mathematical Modeling and Industrial Mathematics. --- Partial Differential Equations. --- Differential equations, partial. --- Biology --- Physiology --- Mathématiques --- Cardiologie --- Cardiovascular system --- Mathematical models. --- Blood -- Diseases. --- Blood flow -- Mathematical models. --- Blood flow. --- Cardiovascular System --- Cardiovascular Physiological Processes --- Blood Physiological Phenomena --- Blood Physiological Processes --- Models, Biological --- Cardiovascular Physiological Phenomena --- Rheology --- Anatomy --- Investigative Techniques --- Circulatory and Respiratory Physiological Phenomena --- Models, Theoretical --- Blood Circulation --- Hemorheology --- Hemodynamics --- Models, Cardiovascular --- Blood Vessels --- Phenomena and Processes --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Engineering & Applied Sciences --- Human Anatomy & Physiology --- Health & Biological Sciences --- Applied Mathematics --- Circulatory system --- Vascular system --- Partial differential equations. --- Applied mathematics. --- Engineering mathematics. --- Biomathematics. --- Mathematical and Computational Biology. --- Blood --- Circulation --- Animal physiology --- Animals --- Heart --- Internal medicine --- Math --- Science --- Partial differential equations --- Diseases --- Models, Mathematical --- Simulation methods --- Mathematics --- Engineering --- Engineering analysis --- Mathematical analysis

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

A major challenge in the modeling and simulation of tumor growth is the mathematical description of living matter, which is far more complex than a mathematical description of inert matter. One critical piece of this challenge is creating multiscale models that take into account subcellular, cellular, and macroscopic levels of cancer. The complexity of these different levels requires the development of new mathematical methods and ideas, which are examined in this work. Written by first-rate researchers in the field of mathematical biology, this collection of selected chapters offers a comprehensive overview of state-of-the-art mathematical methods and tools for modeling and analyzing cancer phenomena. Topics covered include: * Genetic and epigenetic pathways to colon cancer * A game theoretical perspective on the somatic evolution of cancer * Nonlinear modeling and simulation of tumor growth * Tumor cords and their response to anticancer agents * Modeling diffusely invading brain tumors * Multiphase models of tumor growth * Mathematical modeling of breast carcinogenesis * Predictive models in tumor immunology * Multiscale modeling of solid tumor growth Selected Topics in Cancer Modeling is an excellent reference for researchers, practitioners, and graduate students in applied mathematics, mathematical biology, and related fields. The book has an overall aim of quantitative, predictive mathematical modeling of solid tumor growth at all scales, from genetics all the way through to treatment therapy for patients.

Mathematics. --- Oncology. --- Applications of Mathematics. --- Physiological, Cellular and Medical Topics. --- Mathematical Biology in General. --- Mathematical Modeling and Industrial Mathematics. --- Biology --- Physiology --- Mathématiques --- Cancérologie --- Tumors --Growth --Computer simulation. --- Tumors --Growth --Mathematical models. --- Tumors --- Diseases --- Computing Methodologies --- Investigative Techniques --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Information Science --- Models, Theoretical --- Computer Simulation --- Neoplasms --- Medicine --- Health & Biological Sciences --- Oncology --- Growth --- Mathematical models --- Computer simulation --- Computer simulation. --- Mathematical models. --- Tumours --- Health informatics. --- Applied mathematics. --- Engineering mathematics. --- Biomathematics. --- Health Informatics. --- Mathematical and Computational Biology. --- Pathology --- Cysts (Pathology) --- Oncology  . --- Medical records --- Data processing. --- Math --- Science --- Animal physiology --- Animals --- Anatomy --- EHR systems --- EHR technology --- EHRs (Electronic health records) --- Electronic health records --- Electronic medical records --- EMR systems --- EMRs (Electronic medical records) --- Information storage and retrieval systems --- Medical care --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- Clinical informatics --- Health informatics --- Medical information science --- Information science --- Models, Mathematical --- Simulation methods --- Data processing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Computational Neurogenetic Modeling Integrating Bioinformatics and Neuroscience Data, Information and Knowledge via Computational Intelligence Lubica Benuskova and Nikola Kasabov With the presence of a great amount of both brain and gene data related to brain functions and diseases, it is required that sophisticated computational neurogenetic models be created to facilitate new discoveries that will help researchers in understanding the brain in its complex interaction between genetic and neuronal processes. Initial steps in this direction are underway, using the methods of computational intelligence to integrate knowledge, data and information from genetics, bioinfomatics and neuroscience. Computational Neurogenetic Modeling offers the knowledge base for creating such models covering the areas of neuroscience, genetics, bioinformatics and computational intelligence. This multidisciplinary background is then integrated into a generic computational neurogenetic modeling methodology. computational neurogenetic models offer vital applications for learning and memory, brain aging and Alzheimer’s disease, Parkinson’s disease, mental retardation, schizophrenia and epilepsy. Key Topics Include: Brain Information Processing Methods of Computational Intelligence, Including: Artificial Neural Networks Evolutionary Computation Evolving Connectionist Systems Gene Information Processing Methodologies for Building Computational Neurogenetic Models Applications of CNGM for modeling brain functions and diseases Computational Neurogenetic Modeling is essential reading for postgraduate students and researchers in the areas of information sciences, artificial intelligence, neurosciences, bioinformatics and cognitive sciences. This volume is structured so that every chapter can be used as a reading material for research oriented courses at a postgraduate level. About the Authors: Lubica Benuskova is currently Senior Research Fellow at the Knowledge Engineering & Discovery Research Institute (KEDRI, www.kedri.info), Auckland University of Technology (AUT) in Auckland, New Zealand. She is also Associate Professor of Applied Informatics at the Faculty of Mathematics, Physics and Informatics at Comenius (Komensky) University in Bratislava, Slovakia. Her research interests are in the areas of computational neuroscience, cognitive science, neuroinformatics, computer and information sciences. Nikola Kasabov is the Founding Director and Chief Scientist of KEDRI, and a Professor and Chair of Knowledge Engineering at the School of Computer and Information Sciences at AUT. He is a leading expert in computational intelligence and knowledge engineering and has published more than 400 papers, books and patents in the areas of neural and hybrid intelligent systems, bioinformatics and neuroinformatics, speech-, image and multimodal information processing. He is a Fellow of the Royal Society of New Zealand, Senior Member of IEEE, Vice President of the International Neural Network Society and a Past President of the Asia-Pacific Neural Network Assembly.

Engineering. --- Biomedical Engineering. --- Bioinformatics. --- Neurosciences. --- Human Genetics. --- Information Systems and Communication Service. --- Biophysics and Biological Physics. --- Human genetics. --- Information systems. --- Biomedical engineering. --- Ingénierie --- Génétique humaine --- Neurosciences --- Bio-informatique --- Génie biomédical --- Computational neuroscience. --- Neural networks (Computer science). --- Neural networks (Neurobiology). --- Neurogenetics -- Computer simulation. --- Neurogenetics -- Mathematical models. --- Neurogenetics --- Computational neuroscience --- Neural networks (Computer science) --- Neural networks (Neurobiology) --- Diseases --- Mathematical Concepts --- Musculoskeletal and Neural Physiological Phenomena --- Pattern Recognition, Automated --- Computing Methodologies --- Biology --- Models, Biological --- Information Science --- Phenomena and Processes --- Biological Science Disciplines --- Models, Theoretical --- Neural Networks (Computer) --- Nervous System Physiological Phenomena --- Artificial Intelligence --- Computational Biology --- Nervous System Diseases --- Models, Genetic --- Natural Science Disciplines --- Investigative Techniques --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Disciplines and Occupations --- Human Anatomy & Physiology --- Health & Biological Sciences --- Neuroscience --- Biomedical Engineering --- Mathematical models --- Computer simulation --- Information storage and retrieval systems --- Systèmes d'information --- Mathematical models. --- Computer simulation. --- Biological neural networks --- Nets, Neural (Neurobiology) --- Networks, Neural (Neurobiology) --- Neural nets (Neurobiology) --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Computational neurosciences --- Nervous system --- Genetic aspects --- Computers. --- Computational Biology/Bioinformatics. --- Cognitive neuroscience --- Neurobiology --- Neural circuitry --- Artificial intelligence --- Natural computation --- Soft computing --- Computational biology --- Genetics --- Biomedical Engineering and Bioengineering. --- Heredity, Human --- Human biology --- Physical anthropology --- Neural sciences --- Neurological sciences --- Medical sciences --- Bio-informatics --- Biological informatics --- Information science --- Systems biology --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Data processing --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Confabulation theory offers the first complete detailed explanation of the mechanism of cognition, i.e., thinking, an essential information processing capability of all enbrained Earth animals (bees, octopi, trout, ravens, humans, et al.). Concentrating on the human case, this book offers an hypothesis for the neuronal implementation of cognition, and explores the mathematics and methods of application of its mechanism. Thinking turns out to be starkly alien in comparison with all known technological approaches to information processing. While probably not yet scientifically testable, confabulation theory seems consistent with the facts of neuroscience. Beyond science, any complete detailed explanation of cognition can be investigated by applying it technologically. Multiple experiments of this nature are described in this book in complete detail. The results suggest that confabulation theory can provide the universal platform for building intelligent machines. In short, this book explains how thinking works and establishes the foundation for building machines that think. Because of the theory’s implications for philosophy, education, medicine, anthropology and social science, this book will also be of interest to scientists in those domains.

Cerebral cortex. --- Thought and thinking --- Cortex cérébral --- Physiological aspects. --- Thought and thinking -- Physiological aspects. --- Cerebral cortex --- Models, Theoretical --- Cognition --- Investigative Techniques --- Mental Processes --- Psychological Phenomena and Processes --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Psychiatry and Psychology --- Neuroscience --- Human Anatomy & Physiology --- Health & Biological Sciences --- Physiological aspects --- Mind --- Thinking --- Thoughts --- Brain mantle --- Cortex, Cerebral --- Cortex cerebri --- Mantle of brain --- Pallium (Brain) --- Computer science. --- Neurosciences. --- Computers. --- Artificial intelligence. --- Computational linguistics. --- Popular works. --- Cognitive psychology. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Cognitive Psychology. --- Computational Linguistics. --- Popular Science, general. --- Theory of Computation. --- Telencephalon --- Educational psychology --- Philosophy --- Psychology --- Intellect --- Logic --- Perception --- Psycholinguistics --- Self --- Consciousness. --- Science (General). --- Information theory. --- Artificial Intelligence. --- Communication theory --- Communication --- Cybernetics --- Automatic language processing --- Language and languages --- Language data processing --- Linguistics --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Mathematical linguistics --- Multilingual computing --- Apperception --- Mind and body --- Spirit --- Neural sciences --- Neurological sciences --- Medical sciences --- Nervous system --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data processing --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Calculators --- Cyberspace --- Psychology, Cognitive

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book is concerned with the estimation of discrete-time semi-Markov and hidden semi-Markov processes. Semi-Markov processes are much more general and better adapted to applications than the Markov ones because sojourn times in any state can be arbitrarily distributed, as opposed to the geometrically distributed sojourn time in the Markov case. Another unique feature of the book is the use of discrete time, especially useful in some specific applications where the time scale is intrinsically discrete. The models presented in the book are specifically adapted to reliability studies and DNA analysis. The book is mainly intended for applied probabilists and statisticians interested in semi-Markov chains theory, reliability and DNA analysis, and for theoretical oriented reliability and bioinformatics engineers. It can also serve as a text for a six month research-oriented course at a Master or PhD level. The prerequisites are a background in probability theory and finite state space Markov chains. Vlad Stefan Barbu is associate professor in statistics at the University of Rouen, France, Laboratory of Mathematics ‘Raphaël Salem.’ His research focuses basically on stochastic processes and associated statistical problems, with a particular interest in reliability and DNA analysis. He has published several papers in the field. Nikolaos Limnios is a professor in Applied Mathematics at the University of Technology of Compiègne. His research interest concerns stochastic processes and statistics with application to reliability. He is the co-author of the books: Semi-Markov Processes and Reliability (Birkhäuser, 2001 with G. Oprisan) and Stochastic Systems in Merging Phase Space (World Scientific, 2005, with V.S. Koroliuk).

Markov processes --- Reliability (Engineering) --- DNA --- Markov, Processus de --- Fiabilité --- Mathematical models --- Analysis --- Modèles mathématiques --- DNA --Analysis --Mathematical models. --- Markov processes. --- Reliability (Engineering) --Mathematical models. --- Evaluation Studies as Topic --- Probability --- Stochastic Processes --- Epidemiologic Research Design --- Investigative Techniques --- Nucleic Acids --- Statistics as Topic --- Mathematical Concepts --- Nucleic Acids, Nucleotides, and Nucleosides --- Epidemiologic Methods --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Health Care Evaluation Mechanisms --- Quality of Health Care --- Public Health --- Phenomena and Processes --- Chemicals and Drugs --- Environment and Public Health --- Health Care Quality, Access, and Evaluation --- Health Care --- Markov Chains --- Models, Theoretical --- Reproducibility of Results --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Mathematical models. --- Fiabilité --- Modèles mathématiques --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B --- Deoxyribonucleic acid --- Desoxyribonucleic acid --- Thymonucleic acid --- TNA (Nucleic acid) --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Mathematics. --- Bioinformatics. --- Operations research. --- Management science. --- Probabilities. --- Statistics. --- Quality control. --- Reliability. --- Industrial safety. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Quality Control, Reliability, Safety and Risk. --- Operations Research, Management Science. --- Stochastic processes --- Deoxyribose --- Nucleic acids --- Genes --- Distribution (Probability theory. --- Mathematical statistics. --- System safety. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Safety, System --- Safety of systems --- Systems safety --- Accidents --- Industrial safety --- Systems engineering --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Distribution functions --- Frequency distribution --- Characteristic functions --- Data processing --- Prevention --- Statistics . --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Industrial accidents --- Industries --- Job safety --- Occupational hazards, Prevention of --- Occupational health and safety --- Occupational safety and health --- Prevention of industrial accidents --- Prevention of occupational hazards --- Safety, Industrial --- Safety engineering --- Safety measures --- Safety of workers --- System safety --- Dependability --- Trustworthiness --- Conduct of life --- Factory management --- Standardization --- Quality assurance --- Quality of products --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk