Naslov
TAKELAB: Medical Information Extraction and Linking with MINERAL

Autori
Glavaš, Goran

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015) / Nakov, Preslav ; Zesch, Torsten ; Cer, Daniel ; Jurgens, David - Denver (CO) : ACL, 2015, 389-393

Skup
9th International Workshop on Semantic Evaluation (SemEval 2015)

Mjesto i datum
Denver (CO), Sjedinjene Američke Države, 31.05.2015. - 06.06.2015

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
disease extraction; medical information extraction; disease normalization

Sažetak
Medical texts are filled with mentions of diseases, disorders, and other clinical conditions, with many different surface forms relating to the same condition. We describe MINERAL, a system for extraction and normalization of disease mentions in clinical text, with which we participated in the Task 14 of SemEval 2015 evaluation campaign. MINERAL relies on a conditional random fields-based model with a rich set of features for mention detection, and a semantic textual similarity measure for entity linking. MINERAL reaches joint extraction and linking performance of 75.9% relaxed F1- score (strict score of 72.7%) and ranks fourth among 16 participating teams.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA