RUBY: Natural Language Processing of French Electronic Medical Records for Breast Cancer Research.

These results show that the automatic approach has the potential to effectively extract clinical knowledge from an extensive set of electronic medical records, reducing the manual effort required and saving a significant amount of time. A deeper semantic analysis and further understanding of the context in the text, as well as training on a larger and more recent set of reports, including those containing highly variable entities and the use of ontologies, could further improve the results.