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Solidarity in Biomedicine and Beyond, Prainsack


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Автор: Prainsack
Название:  Solidarity in Biomedicine and Beyond
ISBN: 9781107074248
Издательство: Cambridge Academ
Классификация:



ISBN-10: 110707424X
Обложка/Формат: Hardback
Страницы: 256
Вес: 0.51 кг.
Дата издания: 19.01.2017
Серия: Cambridge bioethics and law
Язык: English
Иллюстрации: 4 tables, black and white; 1 halftones, black and white
Размер: 161 x 252 x 2
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Ethics & moral philosophy,Law,Laws of Specific jurisdictions,Social law,Medical & healthcare law,Medical ethics & professional conduct,Bio-ethics, LAW / Medical Law & Legislation
Основная тема: Law
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: In times of global economic and political crises, the notion of solidarity is gaining new currency. Exemplified by three case studies from medicine and health, this book shows how solidarity can make a difference in how we frame problems in biomedicine, and help develop innovative solutions.

Computational Intelligence in Biomedicine and Bioinformatics

Автор: Tomasz G. Smolinski; Mariofanna G. Milanova; Aboul
Название: Computational Intelligence in Biomedicine and Bioinformatics
ISBN: 354070776X ISBN-13(EAN): 9783540707769
Издательство: Springer
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Цена: 204040.00 T
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Описание: Offers an overview of the methodologies that are utilized for biomedicine and/or bioinformatics-oriented applications. This work also includes contributions from researchers applying computational intelligence techniques to important problems in biomedicine and bioinformatics.

Computational Intelligence in Biomedicine and Bioinformatics

Автор: Tomasz G. Smolinski; Mariofanna G. Milanova; Aboul
Название: Computational Intelligence in Biomedicine and Bioinformatics
ISBN: 3642089690 ISBN-13(EAN): 9783642089695
Издательство: Springer
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Цена: 204040.00 T
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Описание: The purpose of this book is to provide an overview of state-of-the-art methodologies currently utilized for biomedicine and/or bioinformatics-oriented applications. Researchers working in these fields will learn new methods to help tackle their problems.

Mathematical Modeling of Biological Systems, Volume I Cellular Biophysics, Regulatory Networks, Development, Biomedicine, and Data Analysis

Автор: Deutsch, A.; Brusch, L.; Byrne, H.; de Vries, G.; Herzel, H. (Eds.)
Название: Mathematical Modeling of Biological Systems, Volume I Cellular Biophysics, Regulatory Networks, Development, Biomedicine, and Data Analysis
ISBN: 0817645578 ISBN-13(EAN): 9780817645571
Издательство: Springer
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Цена: 121110.00 T
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Описание: This edited volume contains a selection of chapters that are an outgrowth of the - ropean Conference on Mathematical and Theoretical Biology (ECMTB05, Dresden, Germany, July 2005). The peer-reviewed contributions show that mathematical and computational approaches are absolutely essential for solving central problems in the life sciences, ranging from the organizational level of individual cells to the dynamics of whole populations. The contributions indicate that theoretical and mathematical biology is a diverse and interdisciplinary ?eld, ranging from experimental research linked to mathema- cal modeling to the development of more abstract mathematical frameworks in which observations about the real world can be interpreted, and with which new hypotheses for testing can be generated. Today, much attention is also paid to the development of ef?cient algorithms for complex computation and visualisation, notably in molecular biology and genetics. The ?eld of theoretical and mathematical biology and medicine has profound connections to many current problems of great relevance to society. The medical, industrial, and social interests in its development are in fact indisputable.

Complex Systems in Biomedicine

Автор: Quarteroni
Название: Complex Systems in Biomedicine
ISBN: 8847003946 ISBN-13(EAN): 9788847003941
Издательство: Springer
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Цена: 121890.00 T
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Описание: Mathematical modeling of human physiopathology is a tremendously ambitious task. It encompasses the modeling of most diverse compartments such as the cardiovascular, respiratory, skeletal and nervous systems, as well as the mechanical and biochemical interaction between blood flow and arterial walls, or electrocardiac processes and the electric conduction into biological tissues. Mathematical models can be set up to simulate both vasculogenesis (the aggregation and organisation of endothelial cells dispersed in a given environment) and angiogenesis (the formation of new vessels sprouting from an existing vessel) that are relevant to the formation of vascular networks, and in particular to the description of tumor growth. The integration of models aimed at simulating the cooperation and interrelation of different systems is an even more difficult task. It calls for the set up of, for instance, interaction models for the integrated cardio-vascular system and the interplay between central circulation and peripheral compartments, models for the mid-long range cardiovascular adjustments to pathological conditions (e.g. to account for surgical interventions, congenital malformations, or tumor growth), models for the integration among circulation, tissue perfusion, biochemical and thermal regulation, models for parameter identification and sensitivity analysis to parameter changes or data uncertainty – and many others. The heart is a complex system in itself, where electrical phenomena are functionally related with the wall deformation. In its turn, electrical activity is related with heart physiology. It involves nonlinear reaction-diffusion processes and provides the activation stimulus to the heart dynamics and eventually the blood ventricular flow that drives the haemodynamics of the whole circulatory system. In fact, the influence is reciprocal, since the circulatory system in turns affects the heart dynamics and may induce an overload depending upon the individual physiopathologies ( for instance the presence of a stenotic artery or a vascular prosthesis).Virtually, all the fields of mathematics have a role to play in this context. Geometry and approximation theory provide the tools for handling clinical data acquired by tomography or magnetic resonance, identifying meaningful geometrical patterns and producing three-dimensional geometrical models stemming from the original patients data. Mathematical analysis, flow and solid dynamics, stochastic analysis are used to set up the differential models and predict uncertainty. Numerical analysis and high performance computing are needed to numerically solve the complex differential models. Finally, methods from stochastic and statistical analysis are exploited for the modeling and interpretation of space-time patterns. Indeed, the complexity of the problems at hand often stimulates the use of innovative mathematical techniques that are able, for instance, to accurately catch those processes that occur at multiple scales in time and space (like cellular and systemic effects), and that are governed by heterogeneous physical laws.


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