A hybrid system for temporal relation extraction from discharge summaries

Abstract

Automatically detecting temporal relations among dates/times and events mentioned in patient records has much potential to help medical staff in understanding disease progression and patients response to treatments. It can also facilitate evidence-based medicine (EBM) research. In this paper, we propose a hybrid temporal relation extraction approach which combines patient-record-specific rules and the Conditional Random Fields (CRFs) model to process patient records.We evaluate our approach on i2b2 dataset, and the results show our approach achieves an F-score of 61%.