Digital twins employ mathematical and computational models to virtually represent a
physical object (eg, planes and human organs), predict the behavior of the object, and …

Introduction: A defining hallmark of cancer is aberrant cell proliferation. Efforts to understand
the generative properties of cancer cells span all biological scales: from genetic deviations …

Brain tumors are one of the major common causes of cancer-related death, worldwide.
Growth prediction of these tumors, particularly gliomas which are the most dominant type …

Despite the remarkable advances in cancer diagnosis, treatment, and management over the
past decade, malignant tumors remain a major public health problem. Further progress in …

A main goal of mathematical and computational oncology is to develop quantitative tools to
determine the most effective therapies for each individual patient. This involves predicting …

Prediction and uncertainty quantification of tumor progression are vital in clinical practice, ie,
disease prognosis and decision-making on treatment strategies. In this work, we propose …

Optimal control theory is branch of mathematics that aims to optimize a solution to a
dynamical system. While the concept of using optimal control theory to improve treatment …

This protocol describes a complete data acquisition, analysis and computational forecasting
pipeline for employing quantitative MRI data to predict the response of locally advanced …

Prognostic tumor growth modeling via volumetric medical imaging observations can
potentially lead to better outcomes of tumor treatment management and surgical planning …

While gliomas have been extensively modelled with a reaction–diffusion (RD) type equation
it is most likely an oversimplification. In this study, three mathematical models of glioma …