https://www.selleckchem.com/MEK.html
PURPOSE Radiomics is a new technique that enables noninvasive prognostic prediction by extracting features from medical images. Homology is a concept used in many branches of algebra and topology that can quantify the contact degree. In the present study, we developed homology-based radiomic features to predict the prognosis of non-small-cell lung cancer (NSCLC) patients and then evaluated the accuracy of this prediction method. METHODS Four datasets were used two to provide training and test data and two for the selection of robust radiomic feature
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