Springer Verlag;Switzerland: Springer International Publishing AG
摘要:
摘要： 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%. 出版者： Switzerland: Springer International Publishing AG 出版日期： 2014 出處： Technologies and Applications of Artificial Intelligence, 2014, Vol.8916, p.379-386 資源來源： Springer Books 版權： Springer International Publishing Switzerland 2014 識別號： ISSN: 0302-9743 識別號： ISBN: 331913986X 識別號： ISBN: 9783319139869 識別號： EISSN: 1611-3349 識別號： EISBN: 3319139878 識別號： EISBN: 9783319139876 識別號： DOI: 10.1007/978-3-319-13987-6_35 識別號： OCLC: 906028264 識別號： LCCallNum: Q334-342TJ210.2-211.
