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The article presents an application of Adaptive Splitting and Selection (AdaSS) ensemble classifier in a real-life task of designing an efficient clinical decision support system for breast cancer malignancy grading. We approach the problem of cancer detection form a different angle - we already know that a given patient has a malignant type of cancer and we want to asses the level of that malignancy...
One of the important problems in medical imaging is two-class classification, for example determination of benign from malignant cases in breast cancer treatment. In this paper we present a new support vector machine method for two-class medical image classification. The key idea of this method is to construct an optimal hypersphere such that both the interior margin between the surface of this sphere...
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. As a result, machine learning is frequently used in cancer diagnosis and detection. In this paper, support vector machines, K-nearest...
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