机译:自动肿瘤识别和数字病理学评分对PD-L1进行了新作用,以预测ER-/ HER2 +乳腺癌的良好结果
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
Horizon Discovery Ltd;
Centre for Cancer Research and Cell Biology;
Horizon Discovery Ltd;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
College of Public Health;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
Centre for Cancer Research and Cell Biology;
机译:自动肿瘤识别和数字病理学评分对PD-L1进行了新作用,以预测ER-/ HER2 +乳腺癌的良好结果
机译:PD-L1免疫组化的有效和全球可重复的数字病理学家培训计划在免疫细胞中的预测生物标志物,用于三重阴性乳腺癌的癌症免疫疗法
机译:AutoIHC评分:ER-和PR染色乳腺癌组织中分子表达自动化评分的机器学习框架
机译:使用深度神经网络对乳腺癌组织病理学图像进行自动核多态性评分。
机译:数字病理的定量组织形态计量学作为辅助诊断:预测ER +乳腺癌的结局。
机译:自动化的肿瘤识别和数字病理评分系统揭示了PD-L1在预测ER- / HER2 +乳腺癌的好结果中的新作用
机译:高血清miR-19a水平与炎性乳腺癌相关,并且预示转移性HER2 +炎性乳腺癌患者的有利临床结果。