Combining rules, background knowledge and change patterns to maintain semantic annotations

Silvio Domingos Cardoso, Reynaud-Delaître Chantal, Marcos Da Silveira, Cédric Pruski
2018 AMIA Annual Symposium Proceedings  
Knowledge Organization Systems (KOS) play a key role in enriching biomedical information in order to make it machine-understandable and shareable. This is done by annotating medical documents, or more specifically, associating concept labels from KOS with pieces of digital information, e.g., images or texts. However, the dynamic nature of KOS may impact the annotations, thus creating a mismatch between the evolved concept and the associated information. To solve this problem, methods to
more » ... the quality of the annotations are required. In this paper, we define a framework based on rules, background knowledge and change patterns to drive the annotation adaption process. We evaluate experimentally the proposed approach in realistic cases-studies and demonstrate the overall performance of our approach in different KOS considering the precision, recall, F1-score and AUC value of the system.
pmid:29854115 pmcid:PMC5977713 fatcat:spefkmcng5h57h5sn4rrqha3hi