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An Introduction to Physical Oncology : How Mechanistic Mathematical Modeling Can Improve Cancer Therapy Outcomes

By: (Author) Eugene Koay , (Author) Vittorio Cristini , (Author) Zhihui Wang

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Ksh 16,550.00

Format: Hardback or Cased Book

ISBN-10: 1466551348

ISBN-13: 9781466551343

Series: Chapman & Hall/CRC Mathematical Biology Series

Publisher: Taylor & Francis Inc

Imprint: CRC Press Inc

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jul 6th, 2017

Print length: 204 Pages

Weight: 592 grams

Dimensions (height x width x thickness): 18.60 x 26.10 x 1.80 cms

Product Classification: Oncology

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This book introduces the emerging field of physical oncology, and includes recent breakthroughs in how novel mathematical models of physical transport processes incorporate patient tissue and imaging data routinely produced in the clinic to predict the efficacy of many cancer treatment approaches, including chemotherapy and radiation therapy.

Physical oncology has the potential to revolutionize cancer research and treatment. The fundamental rationale behind this approach is that physical processes, such as transport mechanisms for drug molecules within tissue and forces exchanged by cancer cells with tissue, may play an equally important role as biological processes in influencing progression and treatment outcome.

This book introduces the emerging field of physical oncology to a general audience, with a focus on recent breakthroughs that help in the design and discovery of more effective cancer treatments. It describes how novel mathematical models of physical transport processes incorporate patient tissue and imaging data routinely produced in the clinic to predict the efficacy of many cancer treatment approaches, including chemotherapy and radiation therapy. By helping to identify which therapies would be most beneficial for an individual patient, and quantifying their effects prior to actual implementation in the clinic, physical oncology allows doctors to design treatment regimens customized to each patient’s clinical needs, significantly altering the current clinical approach to cancer treatment and improving the outcomes for patients.


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