Diagnostic Radiology Text

annotated corpus of 83,452 chest x-ray reports. We show that the distribution of semantics is consistent with Zipfian distributions observed in other natural language corpora, and we quantify the semantic focus imparted by limiting a study by body area and modality. We demonstrate that within our semantically focused corpus, pairwise co-occurrence statistics can be used to accurately impute the semantic class for frequently occurring unknown entities, thereby reducing the number of semantically unclassified phrases by up to 25%. Finally, we show that our imputation approach is consistent across multiple reconstructions of the underlying text data.