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Introduction to Mathematical Oncology

Langbeschreibung
Extensively classroom-tested in undergraduate and graduate courses, this self-contained book presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models.
Inhaltsverzeichnis
Introduction to Theory in Medicine. Introduction to Cancer Modeling. Spatially Structured Tumor Growth. Physiologically Structured Tumor Growth. Prostate Cancer: PSA, AR, and ADT Dynamics. Resource Competition and Cell Quota in Cancer Models. Natural History of Clinical Cancer. Evolutionary Ecology of Cancer. Models of Chemotherapy. Major Anti-Cancer Chemotherapies. Radiation Therapy. Chemical Kinetics. Epilogue: Toward a Quantitative Theory of Oncology.
Yang Kuang is a professor of mathematics at Arizona State University (ASU). Dr. Kuang is the author or editor of more than 150 refereed journal publications and 11 books and the founder and editor of Mathematical Biosciences and Engineering. He is well known for his pioneering work in applying delay differential equation to models of biology and medicine. His recent research interests focus on the formulation of scientifically well-grounded and computationally tractable mathematical models to describe the rich and intriguing dynamics of various within-host diseases and their treatments. These models have the potential to speed up much-needed personalized medicine development. He earned a Ph.D in mathematics from the University of Alberta.
ISBN-13:
9781315361987
Veröffentl:
2018
Seiten:
490
Autor:
Yang Kuang
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
2 - DRM Adobe
Sprache:
Englisch

61,49 €*

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