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Improvement of the Fast Clustering Algorithm Improved by K-Means in the Big Data

) and contained measurements from biopsies of 30 DLBCL patients. Each sample was stained with three antibodies,: CD3, CD5, and CD19. The LunG data [ 44 ] consists of d = 1,000 dimensions with n = 197 lung cancer patients from k = 4 different factors. The Prostate data [ 45 ] consists of d = 12,600 dimensions with n = 102 prostate cancer patients from k = 2 different factors. The original data set from contained 97 men who haved prostate cancer and recorded the information of the patients. Table 3 The date information in the algorithm test

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Applied mathematics and nonlinear sciences in the war on cancer

.g. [ 55 , 56 ] for brain tumors). From the mathematical point of view it is necessary to define meaningful and robust measures of volumes, geometries, textures, etc., to be computed on images providing biomarkers of clinical relevance. Also, images are to be used as initial data for predictive mathematical algorithms able to simulate tumor evolution and provide therapy personalization. Another source of information are blood tests, which allow clinically relevant biomarkers (such as e.g. PSA levels in prostate cancer) to be directly measured. In recent years the

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