Kelly, Liadh and Suominen, Hanna and Goeuriot, Lorraine and Neves, Mariana and Kanoulas, Evangelos and Li, Dan and Azzopardi, Leif and Spijker, Rene and Zuccon, Guido and Scells, Harrisen and Palotti, Joao (2019) Overview of the CLEF eHealth Evaluation Lab 2019. In: Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2019. Lecture Notes in Computer Science book series (LNCS) (11696). Springer, pp. 322-339. ISBN 9783030285777

Preview

Download (199kB) | Preview

Abstract

In this paper, we provide an overview of the seventh annual edition of the CLEF eHealth evaluation lab. CLEF eHealth 2019 continues our evaluation resource building efforts around the easing and support of patients, their next-of-kins, clinical staff, and health scientists in understanding, accessing, and authoring electronic health information in a multilingual setting. This year’s lab advertised three tasks: Task 1 on indexing non-technical summaries of German animal experiments with International Classification of Diseases, Version 10 codes; Task 2 on technology assisted reviews in empirical medicine building on 2017 and 2018 tasks in English; and Task 3 on consumer health search in mono- and multilingual settings that builds on the 2013–18 Information Retrieval tasks. In total nine teams took part in these tasks (six in Task 1 and three in Task 2). Herein, we describe the resources created for these tasks and evaluation methodology adopted. We also provide a brief summary of participants of this year’s challenges and results obtained. As in previous years, the organizers have made data and tools associated with the lab tasks available for future research and development.

Item Type:	Book Section
Additional Information:	Cite as: Kelly L. et al. (2019) Overview of the CLEF eHealth Evaluation Lab 2019. In: Crestani F. et al. (eds) Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2019. Lecture Notes in Computer Science, vol 11696. Springer, Cham. https://doi.org/10.1007/978-3-030-28577-7_26
Keywords:	Evaluation; Entity linking; Information retrieval; Health records; High recall; Information extraction; Medical informatics; Self diagnosis; Systematic reviews; Test set generation; Text classification; Text segmentation;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Science and Engineering > Research Institutes > Human Health Institute
Item ID:	14368
Depositing User:	Liadh Kelly
Date Deposited:	22 Apr 2021 14:29
Publisher:	Springer
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads