Deep learning can be used to predict genomic alterations on the basis of morphological features learned from digital histopathology. Two independent pan-cancer studies now show that automated learning from digital pathology slides and genomics can potentially delineate broader classes of molecular signatures and prognostic associations across cancer types.

中文翻译：

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深度学习将癌症的组织学、分子特征和预后联系起来

深度学习可用于根据从数字组织病理学中学习到的形态特征来预测基因组改变。现在，两项独立的泛癌研究表明，从数字病理切片和基因组学中自动学习可以潜在地描绘更广泛类别的分子特征和跨癌症类型的预后关联。