Recognizing UMLS Semantic Types with Deep Learning

no code implementations • WS 2019 • Isar Nejadgholi, Kathleen C. Fraser, Berry De Bruijn, Muqun Li, Astha LaPlante, Khaldoun Zine El Abidine

While producing a state-of-the-art result for the i2b2 2010 task (F1 = 0. 90), our results on MedMentions are significantly lower (F1 = 0. 63), suggesting there is still plenty of opportunity for improvement on this new data.

Entity Linking Relation Extraction +2

Extracting UMLS Concepts from Medical Text Using General and Domain-Specific Deep Learning Models

no code implementations • 3 Oct 2019 • Kathleen C. Fraser, Isar Nejadgholi, Berry de Bruijn, Muqun Li, Astha LaPlante, Khaldoun Zine El Abidine

While producing a state-of-the-art result for the i2b2 2010 task (F1 = 0. 90), our results on MedMentions are significantly lower (F1 = 0. 63), suggesting there is still plenty of opportunity for improvement on this new data.

Entity Linking Relation Extraction +2