TCGA-BRCA
PulseAugur coverage of TCGA-BRCA — every cluster mentioning TCGA-BRCA across labs, papers, and developer communities, ranked by signal.
1 天有情绪数据
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New PPLS framework offers calibrated uncertainty and improved accuracy
Researchers have developed a new framework for Probabilistic Partial Least Squares (PPLS) that addresses practical limitations in existing fitting pipelines. This framework combines noise pre-estimation, constrained lik…
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Study finds feature dimensionality more critical than model complexity for breast cancer classification
A new study published on arXiv evaluates machine learning models for classifying breast cancer subtypes using gene expression data from TCGA-BRCA. The research found that feature dimensionality significantly impacts cla…
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SCOUT transformer generates concept-grounded pathology reports from whole-slide images
Researchers have developed SCOUT, a novel multimodal transformer framework designed for generating concept-grounded pathology reports from whole-slide images. This approach integrates local histological patterns, whole-…
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深度学习从病理图像预测乳腺癌亚型
研究人员开发了一个新的深度学习框架，使用组织病理学图像对乳腺癌亚型进行分类，有可能减少对昂贵分子检测的需求。该方法采用多目标斑块选择策略，结合遗传算法和不确定性估计，以识别用于分类的信息性图像斑块。该方法在内部和外部数据集上均取得了较高的F1分数和AUC值，证明了其通过提供计算效率高、基于成像的替代方案来支持临床决策的潜力。