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The article "Bayesian Spatio-Temporal prediction of cancer dynamics", published in Computers and Mathematics with Applications,
is one of the prediction methods implemented in PreDySEC software. Using a prediction method and comparison with the real
evolution (from analysis) a physician can observe if the prescribed treatment has the desired effect. The development of tumor models
is important as they offer a way to better understand the kinetic growth of malignant tumors which may lead to the development of
successful treatment strategies. My PhD research theme was to observe the dynamic of cancer tumors and to develop and implement
new methods and algorithms for prediction of tumour growth. In this sense, I developed three methods of prediction and I plan to
develop a new logical algorithm to predict the growing tumors in time and space. All these methods were implementing in PreDySEC
(Prediction of Dynamic Shape Evolution of Cancer) software - a Matlab interface of mathematical algorithms. The mathematical
methods and the research result of prediction are published in the following articles:
- Bayesian Spatio-Temporal prediction of cancer dynamics
- Two handy geometric prediction methods of cancer growth
- A geometric approach to cancer growth prediction based on Cox processes
I plan to develop the PreDySEC and offer an online platform for this software with friendly and easy-to-use graphical interface.