cancer; cellular biophysics; decision support systems; evolutionary computation; feature selection; fuzzy set theory; image classification; image segmentation; medical image processing; AdaSS ensemble classifier; adaptive splitting and selection ensemble; breast cancer malignancy grading; cancer detection; clinical decision support system; cytological image segmentation process; decision space; evolutionary splitting; feature selection; fuzzy c-means procedure; hybrid combined classifier; hybrid training algorithm; imbalanced classification problem; object space; real-life task; support function; trained weighted fusion; Biological cells; Breast cancer; Feature extraction; Image segmentation; Training; Vectors; cancer classification; classifier ensemble; clinical decision support; hybrid classifier; imbalanced classification; medical image processing; pattern classification;
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机译:导管乳腺癌中Ki-67和MCM-2增殖标志物表达与组织恶性程度(G)的相关性。
机译:乳腺癌恶性分级的自适应分裂与选择合奏
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机译:集合分类器方法在乳腺癌检测和恶性肿瘤中的应用 评分 - 评论