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Books on the topic 'Heart Sounds Mathematical models'

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Published: 4 June 2021
Last updated: 6 February 2022

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1

Beer, Stafford. The heart of enterprise. Chichester: John Wiley & Sons, 1994.

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2

Schroter, V. STEAM, Sound from Trains Environmental Analysis Method. [Toronto]: Ontario Ministry of the Environment, 1990.

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3

Schroter, V. STEAM, sound from trains environmental analysis method: Report. [Ontario]: Queen's Printer for Ontario, 1990.

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4

K, Cheng Leo, and Buist Martin L, eds. Mathematical modelling the electrical activity of the heart: From cell to body surface and back again. New Jersey: World Scientific, 2005.

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5

1943-, Othmer H. G., and National Science Foundation (U.S.), eds. Some mathematical questions in biology: The dynamics of excitable media. Providence, R.I: American Mathematical Society, 1989.

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6

Darowski, Marek. Comprehensive models of cardiovascular and respiratory systems: Their mechanical support and interactions. New York: Nova Science, 2010.

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7

Kantor, B. I͡A. Nelineĭnai͡a kardiobiomekhanika levogo zheludochka. Kiev: Nauk. dumka, 1991.

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8

service), SpringerLink (Online, ed. Introduction to Computational Cardiology: Mathematical Modeling and Computer Simulation. Boston, MA: Springer Science+Business Media, LLC, 2010.

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9

K, Dana Syamal, Roy Prodyot K, and Kurths J. (Jürgen) 1953-, eds. Complex dynamics in physiological systems: From heart to brain. [Dordrecht]: Springer, 2009.

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10

Titomir, L. I. Bioelectric and biomagnetic fields: Theory and applications in electrocardiology. Boca Raton: CRC Press, 1994.

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11

Kantor, B. I͡A. Noninvasive diagnostics of the left heart: Biomechanical disturbances. Commack, N.Y: Nova Science Publishers, 1995.

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12

Engineering hemodynamics: Application to cardiac assist devices. 2nd ed. New York: New York University Press, 1987.

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13

International School of Biophysics (1997 Casamicciola Terme, Italy). Chaos and noise in biology and medicine: Proceedings of the International School of Biophysics, Casamicciola, Napoli, Italy, 19-24 May 1997. Singapore: World Scientific, 1998.

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14

Sarma, Syam. The gemfibrozil cost-benefit model: Analysis of data from the Helsinki Heart Study, model development, and extension to the California Medicaid population. Santa Monica, CA (1700 Main St., P.O. Box 2138, Santa Monica 90407-2138): RAND, 1993.

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15

Sarma, Syam. The gemfibrozil cost-benefit model: Analysis of data from the Helsinki Heart Study, model development, and extension to the California Medicaid population. Santa Monica, CA (1700 Main St., P.O. Box 2138, Santa Monica 90407-2138): RAND, 1993.

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16

Sarma, Syam. The gemfibrozil cost-benefit model: Analysis of data from the Helsinki Heart Study, model development, and extension to the California Medicaid population. Santa Monica, CA (1700 Main St., P.O. Box 2138, Santa Monica 90407-2138): RAND, 1993.

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17

Sarma, Syam. The gemfibrozil cost-benefit model: Analysis of data from the Helsinki Heart Study, model development, and extension to the California Medicaid population. Santa Monica, CA: RAND, 1993.

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18

Sarma, Syam. The gemfibrozil cost-benefit model: Analysis of data from the Helsinki Heart Study, model development, and extension to the California Medicaid population. Santa Monica, CA (1700 Main St., P.O. Box 2138, Santa Monica 90407-2138): RAND, 1993.

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19

Rocşoreanu, C. The FitzHugh-Nagumo model: Bifurcation and dynamics. Dordrecht: Kluwer Academic Publishers, 2000.

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20

1944-, Matsumoto T., ed. Bifurcations: Sights, sounds, and mathematics. Tokyo: Springer, 1993.

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21

Matsumoto, T., M. Komuro, H. Kokubu, and R. Tokunaga. Bifurcations: Sights, Sounds, and Mathematics. Springer, 1993.

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22

V, Panfilov Alexander, and Holden Arun V. 1947-, eds. Computational biology of the heart. Chichester: Wiley, 1997.

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23

Heydari, Simin. Pressure response of harmonically driven isolated heart. 1992.

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24

José, Jalife, and New York Academy of Sciences., eds. Mathematical approaches to cardiac arrhythmias. New York, N.Y: New York Academy Sciences, 1990.

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25

A, Amini Amir, and Prince Jerry L, eds. Measurement of cardiac deformations from MRI: Physical and mathematical models. Dordrecht: Kluwer Academic Publishers, 2001.

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26

United States. National Aeronautics and Space Administration., ed. Incompressible viscous flow computations for the pump components and the artificial heart. San Jose, CA: MCAT Institute, 1992.

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27

S, Sideman, and Beyar Rafael, eds. Analytical and quantitative cardiology. New York: Plenum Press, 1997.

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28

Analytical and Quantitative Cardiology. Springer, 2012.

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29

1943-, Glass Leon, Hunter Peter 1948-, McCulloch Andrew 1961-, and Institute for Nonlinear Science, eds. Theoryof heart: Biomechanics, biophysics, and nonlinear dynamics of cardiac function. New York: Springer-Verlag, 1991.

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30

Pullan, Andrew J., Leo K. Cheng, and Martin L. Buist. Mathematically Modeling the Electrical Activity of the Heart: From Cell to Body Surface and Back. World Scientific Publishing Company, 2005.

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31

1943-, Glass Leon, Hunter Peter 1948-, McCulloch Andrew, and Institute for Nonlinear Science, eds. Theory of heart: Biomechanics, biophysics, and nonlinear dynamics of cardiac function. New York: Springer-Verlag, 1991.

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32

Hunter, Peter, and Leon Glass. Theory of Heart: Biomechanics, Biophysics, and Nonlinear Dynamics of Cardiac Function (Institute for Non-Linear Science). Springer, 1991.

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33

1957-, He Bin, ed. Modeling and imaging of bioelectrical activity: Principles and applications. New York: Kluwer Academic/Plenum Publishers, 2004.

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34

(Editor), J. T. Ottesen, and M. Danielsen (Editor), eds. Mathematical Modelling in Medicine (Studies in Health Technology and Informatics, 71). IOS Press, 2000.

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35

Kantor, B. Ia, N. I. Iabluchanskii, and A. V. Martynenko. Noninvasive Diagnostics of the Left Heart: Biomechanical Disturbances. Nova Science Pub Inc, 1996.

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36

The science of disasters: Climate disruptions, heart attacks, and market crashes. Berlin: Springer, 2002.

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37

I, Kitney R., and Rompelman O, eds. The Beat-by-beat investigation of cardiovascular function: Measurement, analysis, and applications. Oxford: Clarendon Press, 1987.

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38

Computational Cardiology: Modeling of Anatomy, Electrophysiology, and Mechanics (Lecture Notes in Computer Science). Springer, 2004.

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39

A, Holzapfel Gerhard, and Ogden R. W. 1943-, eds. Biomechanical modelling at the molecular, cellular, and tissue levels. Wien: Springer, 2009.

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40

Buchwald, Jed Z., and Robert Fox. Introduction. Edited by Jed Z. Buchwald and Robert Fox. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199696253.013.1.

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This Handbook looks at the history of physics since the seventeenth century. It is comprised of four sections, the first of which discusses the place of reason, mathematics, and experiment in the age of the scientific revolution. The first section also covers the contributions of Galileo, René Descartes, and Isaac Newton. The second section deals with the ‘long’ eighteenth century — a period that is often regarded as synonymous with the ‘age of Newton’. The third section encompasses the subcategories of heat, light, electricity, sound, and magnetism, while the fourth and final section takes us into the age of ‘modern physics’, highlighted by landmark achievements such as the discovery of the photoelectric effect in 1887, Max Planck’s work on the quanta of radiation, Albert Einstein’s special theory of relativity of 1905, and the elaboration of the various aspects of what became known as quantum physics between 1900 and 1930.
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41

Sundnes, Joakim, Glenn Terje Lines, Xing Cai, Kent-Andre Mardal, Aslak Tveito, and Bjørn Frederik Nielsen. Computing the Electrical Activity in the Heart. Springer, 2010.

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42

Joakim, Sundnes, ed. Computing the electrical activity in the heart. Berlin: Springer, 2006.

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43

Georgescu, A., C. Rocsoreanu, and N. Giurgiteanu. The FitzHugh-Nagumo Model - Bifurcation and Dynamics (MATHEMATICAL MODELLING: THEORY AND APPLICATIONS Volume 10). Springer, 2000.

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44

(Editor), K. Perktold, and P. Verdonck (Editor), eds. Intra and Extracorporeal Cardiovascular Fluid Dynamics: Vol. 2 - Fluid Structure Interaction (Advances in Fluid Mechanics). WIT Press (UK), 2000.

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45

P, Verdonck, and Perktold K, eds. Intra and extracorporeal cardiovascular fluid dynamics. Southampton: Computational Mechanics Publications, 1998.

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46

(Editor), K. Perktold, and P. Verdonck (Editor), eds. Intra and Extracorporeal Cardiovascular Fluid Dynamics (Advances in Fluid Mechanics). 2nd ed. WIT Press (UK), 2000.

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47

Tveito, Aslak, Joakim Sundnes, Glenn Terje Lines, Xing Cai, Bjørn Fredrik Nielsen, and Kent-Andre Mardal. Computing the Electrical Activity in the Heart (Monographs in Computational Science and Engineering). Springer, 2006.

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48

Coolen, Ton, Alessia Annibale, and Ekaterina Roberts. Generating Random Networks and Graphs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.001.0001.

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This book supports researchers who need to generate random networks, or who are interested in the theoretical study of random graphs. The coverage includes exponential random graphs (where the targeted probability of each network appearing in the ensemble is specified), growth algorithms (i.e. preferential attachment and the stub-joining configuration model), special constructions (e.g. geometric graphs and Watts Strogatz models) and graphs on structured spaces (e.g. multiplex networks). The presentation aims to be a complete starting point, including details of both theory and implementation, as well as discussions of the main strengths and weaknesses of each approach. It includes extensive references for readers wishing to go further. The material is carefully structured to be accessible to researchers from all disciplines while also containing rigorous mathematical analysis (largely based on the techniques of statistical mechanics) to support those wishing to further develop or implement the theory of random graph generation. This book is aimed at the graduate student or advanced undergraduate. It includes many worked examples, numerical simulations and exercises making it suitable for use in teaching. Explicit pseudocode algorithms are included to make the ideas easy to apply. Datasets are becoming increasingly large and network applications wider and more sophisticated. Testing hypotheses against properly specified control cases (null models) is at the heart of the ‘scientific method’. Knowledge on how to generate controlled and unbiased random graph ensembles is vital for anybody wishing to apply network science in their research.
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