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CLEF eHealth Evaluation Lab 2020
Laypeople’s increasing difficulties to retrieve and digest valid and relevant information in their preferred language to make health-centred decisions has motivated CLEF eHealth to organize yearly labs since 2012. These 20 evaluation tasks on Information Extraction (IE), management, and Information...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148004/ http://dx.doi.org/10.1007/978-3-030-45442-5_76 |
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author | Suominen, Hanna Kelly, Liadh Goeuriot, Lorraine Krallinger, Martin |
author_facet | Suominen, Hanna Kelly, Liadh Goeuriot, Lorraine Krallinger, Martin |
author_sort | Suominen, Hanna |
collection | PubMed |
description | Laypeople’s increasing difficulties to retrieve and digest valid and relevant information in their preferred language to make health-centred decisions has motivated CLEF eHealth to organize yearly labs since 2012. These 20 evaluation tasks on Information Extraction (IE), management, and Information Retrieval (IR) in 2013–2019 have been popular—as demonstrated by the large number of team registrations, submissions, papers, their included authors, and citations (748, 177, 184, 741, and 1299, respectively, up to and including 2018)—and achieved statistically significant improvements in the processing quality. In 2020, CLEF eHealth is calling for participants to contribute to the following two tasks: The 2020 Task 1 on IE focuses on term coding for clinical textual data in Spanish. The terms considered are extracted from clinical case records and they are mapped onto the Spanish version of the International Classification of Diseases, the 10th Revision, including also textual evidence spans for the clinical codes. The 2020 Task 2 is a novel extension of the most popular and established task in CLEF eHealth on CHS. This IR task uses the representative web corpus used in the 2018 challenge, but now also spoken queries, as well as textual transcripts of these queries, are offered to the participants. The task is structured into a number of optional subtasks, covering ad-hoc search using the spoken queries, textual transcripts of the spoken queries, or provided automatic speech-to-text conversions of the spoken queries. In this paper we describe the evolution of CLEF eHealth and this year’s tasks. The substantial community interest in the tasks and their resources has led to CLEF eHealth maturing as a primary venue for all interdisciplinary actors of the ecosystem for producing, processing, and consuming electronic health information. |
format | Online Article Text |
id | pubmed-7148004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71480042020-04-13 CLEF eHealth Evaluation Lab 2020 Suominen, Hanna Kelly, Liadh Goeuriot, Lorraine Krallinger, Martin Advances in Information Retrieval Article Laypeople’s increasing difficulties to retrieve and digest valid and relevant information in their preferred language to make health-centred decisions has motivated CLEF eHealth to organize yearly labs since 2012. These 20 evaluation tasks on Information Extraction (IE), management, and Information Retrieval (IR) in 2013–2019 have been popular—as demonstrated by the large number of team registrations, submissions, papers, their included authors, and citations (748, 177, 184, 741, and 1299, respectively, up to and including 2018)—and achieved statistically significant improvements in the processing quality. In 2020, CLEF eHealth is calling for participants to contribute to the following two tasks: The 2020 Task 1 on IE focuses on term coding for clinical textual data in Spanish. The terms considered are extracted from clinical case records and they are mapped onto the Spanish version of the International Classification of Diseases, the 10th Revision, including also textual evidence spans for the clinical codes. The 2020 Task 2 is a novel extension of the most popular and established task in CLEF eHealth on CHS. This IR task uses the representative web corpus used in the 2018 challenge, but now also spoken queries, as well as textual transcripts of these queries, are offered to the participants. The task is structured into a number of optional subtasks, covering ad-hoc search using the spoken queries, textual transcripts of the spoken queries, or provided automatic speech-to-text conversions of the spoken queries. In this paper we describe the evolution of CLEF eHealth and this year’s tasks. The substantial community interest in the tasks and their resources has led to CLEF eHealth maturing as a primary venue for all interdisciplinary actors of the ecosystem for producing, processing, and consuming electronic health information. 2020-03-24 /pmc/articles/PMC7148004/ http://dx.doi.org/10.1007/978-3-030-45442-5_76 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Suominen, Hanna Kelly, Liadh Goeuriot, Lorraine Krallinger, Martin CLEF eHealth Evaluation Lab 2020 |
title | CLEF eHealth Evaluation Lab 2020 |
title_full | CLEF eHealth Evaluation Lab 2020 |
title_fullStr | CLEF eHealth Evaluation Lab 2020 |
title_full_unstemmed | CLEF eHealth Evaluation Lab 2020 |
title_short | CLEF eHealth Evaluation Lab 2020 |
title_sort | clef ehealth evaluation lab 2020 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148004/ http://dx.doi.org/10.1007/978-3-030-45442-5_76 |
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