TY - GEN
T1 - CLEF eHealth Evaluation Lab 2021
AU - Goeuriot, Lorraine
AU - Suominen, Hanna
AU - Kelly, Liadh
AU - Alemany, Laura Alonso
AU - Brew-Sam, Nicola
AU - Cotik, Viviana
AU - Filippo, Darío
AU - Gonzalez Saez, Gabriela
AU - Luque, Franco
AU - Mulhem, Philippe
AU - Pasi, Gabriella
AU - Roller, Roland
AU - Seneviratne, Sandaru
AU - Vivaldi, Jorge
AU - Viviani, Marco
AU - Xu, Chenchen
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Motivated by the ever increasing difficulties faced by laypeople in retrieving and digesting valid and relevant information to make health-centred decisions, the CLEF eHealth lab series has offered shared tasks to the community in the fields of Information Extraction (IE), management, and Information Retrieval (IR) since 2013. These tasks have attracted large participation and led to statistically significant improvements in processing quality. In 2021, CLEF eHealth is calling for participants to contribute to the following two tasks: Task 1 on IE focuses on IE from noisy text. Participants will identify and classify Named Entities in written ultrasonography reports, containing misspellings and inconsistencies, from a major public hospital in Argentina. Identified entities will then have to be classified, which can be very challenging as it requires to handle lexical variations. Task 2 is a novel extension of the most popular and established task on consumer health search (CHS), aiming at retrieving relevant, understandable, and credible information for patients and their next-of-kins. In this paper we describe recent advances in the fields of IE and IR, and the subsequent offerings of this years CLEF eHealth lab challenges.
AB - Motivated by the ever increasing difficulties faced by laypeople in retrieving and digesting valid and relevant information to make health-centred decisions, the CLEF eHealth lab series has offered shared tasks to the community in the fields of Information Extraction (IE), management, and Information Retrieval (IR) since 2013. These tasks have attracted large participation and led to statistically significant improvements in processing quality. In 2021, CLEF eHealth is calling for participants to contribute to the following two tasks: Task 1 on IE focuses on IE from noisy text. Participants will identify and classify Named Entities in written ultrasonography reports, containing misspellings and inconsistencies, from a major public hospital in Argentina. Identified entities will then have to be classified, which can be very challenging as it requires to handle lexical variations. Task 2 is a novel extension of the most popular and established task on consumer health search (CHS), aiming at retrieving relevant, understandable, and credible information for patients and their next-of-kins. In this paper we describe recent advances in the fields of IE and IR, and the subsequent offerings of this years CLEF eHealth lab challenges.
KW - Information extraction
KW - Information storage and retrieval
KW - Medical informatics
KW - eHealth
UR - http://www.scopus.com/inward/record.url?scp=85107385710&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-72240-1_69
DO - 10.1007/978-3-030-72240-1_69
M3 - Conference contribution
SN - 9783030722395
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 593
EP - 600
BT - Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR 2021, Proceedings
A2 - Hiemstra, Djoerd
A2 - Moens, Marie-Francine
A2 - Mothe, Josiane
A2 - Perego, Raffaele
A2 - Potthast, Martin
A2 - Sebastiani, Fabrizio
PB - Springer Science and Business Media Deutschland GmbH
T2 - 43rd European Conference on Information Retrieval, ECIR 2021
Y2 - 28 March 2021 through 1 April 2021
ER -