NCU IISR System for NTCIR-11 MedNLP-2 Task
Shengwei Chen, Po‐Ting Lai, Yi‐Lin Tsai, Jay Kuan-Chieh Chung, Sherry Shih-Huan Hsiao, Richard Tzong‐Han Tsai · 2014
mentions and temporal expressions. We also use CRFs to detect the modalities of the ICD-10 mentions. To resolve the problem of ICD-10 mention normalization, we use the Lucene engine to link mentions to the corresponding ICD-10 database entries. Evaluated on the MedNLP test set, our system achieved f-scores of 79.96 % for ICD-10 term recognition, 67.64 % for time expression and 69.4 % for ICD-10 mention normalization.