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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...

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Detalles Bibliográficos
Autores principales: Suominen, Hanna, Kelly, Liadh, Goeuriot, Lorraine, Krallinger, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148004/
http://dx.doi.org/10.1007/978-3-030-45442-5_76
Descripción
Sumario: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.