肿瘤学：When perfect is a warning: explanations expose shortcuts that accuracy hides in cancer gene-expression classifiers

原文摘录：When the classes in a training set come from different data sources, a classifier can score near-perfectly while learning where a sample came from. … It raised no false alarms, ranked models by their real reliance on the source, transferred to unseen model types and data, and failed where its theory predicts