Mathematical Modeling of Atherosclerosis, Cancer, and Diabetes : Analysis and Simulation
by
Xuming Xie
Book Details
Format
Hardback or Cased Book
Book Series
Chapman & Hall/CRC Mathematical Biology Series
ISBN-10
1032453206
ISBN-13
9781032453200
Publisher
Taylor & Francis Ltd
Imprint
Chapman & Hall/CRC
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Aug 25th, 2026
Print length
300 Pages
Product Classification:
Infectious & contagious diseasesInfectious and contagious diseasesMathematical modelling
Ksh 20,700.00
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This book provides state of art mathematical models describing the dynamical behaviour of diabetes, atherosclerosis and cancer. It is aimed at professional mathematical analysts, applied mathematicians, biophysicists and biomedical engineers. It can also be used to teach graduate students.
Diabetes, atherosclerosis, and cancer are the three diseases that contribute to most morbidity and mortality in the world. Mathematical Modeling of Atherosclerosis, Cancer, and Diabetes: Analysis and Simulation provides state-of-art mathematical models describing the dynamical behavior of these three diseases, focusing not only on numerical simulations but also on the mathematical analysis of the models themselves. Mathematical analysis in this context means rigorously studying some theoretical issues such as the ‘well-posedness’ of the models, steady solution, and their stability, and asymptotical behavior of the solutions. The book is aimed at professional mathematical analysts, applied mathematicians, biophysicists, and biomedical engineers. The book can be used to teach graduate students, while it should be valuable reference for researchers in mathematical biology, dynamical systems, PDEs, and stochastic differential equations. FeaturesCollects the most recent research on both mathematical analysis and numerical simulation of mathematical models for diabetes, atherosclerosis, and cancerIncludes both analysis and simulation of stochastic models for the diseasesProvides a self-contained review of dynamical systems, partial differential equations, and stochastic differential equationsSoftware code for readers who wish to practice data on any one of the existing models. The code is available in the programming languages of MATLAB® and/or Python.
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