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1 University of Pittsburg 2 Stockholm University 3 University of Utah 4 University of Melbourne 5 DCU - Dublin City University Dublin 6 Université Grenoble Alpes Saint Martin d-Hères 7 Columbia University New York 8 Harvard University Cambridge

Abstract : This paper reports on Task 2 of the 2014 ShARe-CLEF eHealth evaluation lab which extended Task 1 of the 2013 ShARe-CLEF eHealth evaluation lab by focusing on template filling of disorder at-tributes. The task was comprised of two subtasks: attribute normaliza-tion task 2a and cue identification task 2b. We instructed participants to develop a system which either kept or updated a default attribute value for each task. Participant systems were evaluated against a blind reference standard of 133 discharge summaries using Accuracy task 2a and F-score task 2b. In total, ten teams participated in task 2a, and three teams in task 2b. For task 2a and 2b, the HITACHI team systems run 2 had the highest performances, with an overall average average accuracy of 0.868 and F1-score strict of 0.676, respectively.

Keywords : Information Ex-traction Clinical Text Natural Language Processing Template Filling





Autor: Danielle L. Mowery - Sumithra Velupillai - Brett R. South - Lee Christensen - David Martinez - Liadh Kelly - Lorraine Goeuriot -

Fuente: https://hal.archives-ouvertes.fr/



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