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We find that type I error rates can be well-controlled and MiATDS shows superior efficiency on the power. By applying to real data analysis, MiATDS displays reliable practicability too. The R package is available at https//github.com/XiaoyunHuang33/MiATDS. We aim to build an accurate machine learning-based system for classifying tumor attributes from cancer pathology reports in the presence of a small amount of annotated data, motivated by the expensive and time-consuming nature of pathology report annotation. An enriched labeling scheme tha
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