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The goal of this paper is to show the use of data mining techniques to predict the Soft Tissue Sarcoma (STS) tumor progression. STS are cancers which occur in different parts of the body such as fat, muscle and nerves. The lack of effective treatments and the difficulty in predicting treatment response make them challenging for physicians, and has likely slowed the evolution of new therapeutic agents...
Soft Tissue Sarcomas (STS) are malignant tumors which emanate from soft tissues of the body. They are challenging for physicians because of the infrequency of their occurrence and non-predictable outcomes. In this paper, we propose a novel framework to classify STS which focuses on radio logically defined sub-regions, so-called 'habitats'. The distinctive habitats are regions where tumor evolution...
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