The Semantic Knowledge Extractor Tool (SKET) is an unsupervised hybrid knowledge extraction system that combines a rule-based expert system with pre-trained machine learning models to extract cancer-related information from pathology reports. The code is available in its GitHub repository. Sket is currently used by the ExaMode partners to extract entities from medical reports and to … Continue reading SKET