Abstract
Many scientific problems have been solved using mathematical models. Using mathematical models to simulate dynamic biological processes has a long history. A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. Over the past couple of decades or so, quantitative approaches have also made their way into cancer research. An increasing number of mathematical, physical, computational and engineering techniques have been applied to various aspects of tumor growth. Here we propose the use of emerging, quantitative tumour imaging methods to initialize a new generation of predictive models.
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