Abstract
In this paper, we provide an overview of the eight annual edition of the Conference and Labs of the Evaluation Forum (CLEF) eHealth evaluation lab. The Conference and Labs of the Evaluation Forum (CLEF) eHealth 2020 continues our development of evaluation tasks and resources since 2012 to address laypeople’s difficulties to retrieve and digest valid and relevant information in their preferred language to make health-centred decisions. This year’s lab advertised two tasks. Task 1 on Information Extraction (IE) was new and focused on automatic clinical coding of diagnosis and procedure the tenth revision of the International Statistical Classification of Diseases and Related Health Problems (ICD10) codes as well as finding the corresponding evidence text snippets for clinical case documents in Spanish. Task 2 on Information Retrieval (IR) was a novel extension of the most popular and established task in the Conference and Labs of the Evaluation Forum (CLEF) eHealth on Consumer Health Search (CHS). In total 55 submissions were made to these tasks. Herein, we describe the resources created for the two tasks and evaluation methodology adopted. We also summarize lab submissions and results. As in previous years, the organizers have made data and tools associated with the lab tasks available for future research and development. The ongoing substantial community interest in the tasks and their resources has led to the Conference and Labs of the Evaluation Forum (CLEF) eHealth maturing as a primary venue for all interdisciplinary actors of the ecosystem for producing, processing, and consuming electronic health information.
With equal contribution, LG, HS & LK co-chaired the lab. The leaders of Task 1 were AM-E and MK. The leaders of Task 2 were LG and HS, with LK, ZL, GP, GGS, MV, and CX as co-organizers and contributors to the evaluation conceptualization, dataset creation, assessments, and measurements.
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Notes
- 1.
The CodiEsp corpus, together with the other generated resources are available at the Medical Natural Language Processing (NLP) Zenodo community, https://zenodo.org/communities/medicalnlp/ and at the shared task webpage, https://temu.bsc.es/codiesp/.
- 2.
“Expressing an interest" for a CLEF task consists of filling in a form on the CLEF conference website with contact information, and tick boxes corresponding to the labs of interest.
- 3.
https://clefehealth.imag.fr/ (last accessed on 19 June 2020).
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Acknowledgements
We gratefully acknowledge the contribution of the people and organizations involved in CLEF eHealth in 2012–2020 as participants or organizers. We thank the CLEF Initiative, Benjamin Lecouteux (Université Grenoble Alpes), João Palotti (Qatar Computing Research Institute), and Guido Zuccon (University of Queensland). We also thank the individuals who generated spoken queries for the IR challenge. We are very grateful to our assessors that helped despite the COVID-19 crisis: Paola Alberti, Vincent Arnone, Nathan Baran, Pierre Barbe, Francesco Bartoli, Nicola Brew-Sam, Angela Calabrese, Sabrina Caldwell, Daniele Cavalieri, Madhur Chhabra, Luca Cuffaro, Yerbolat Dalabayev, Emine Darici, Marco Di Sarno, Mauro Guglielmo, Weiwei Hou, Yidong Huang, Zhengyang Liu, Federico Moretti, Marie Revet, Paritosh Sharma, Haozhan Sun, Christophe Zeinaty. The lab has been supported in part by (in alphabetical order) The Australian National University, College of Engineering and Computer Science, Research School of Computer Science; and the CLEF Initiative. We acknowledge the Encargo of Plan TL (SEAD) to CNIO and BSC for funding, and the scientific committee for their valuable comments and guidance.
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Goeuriot, L. et al. (2020). Overview of the CLEF eHealth Evaluation Lab 2020. In: Arampatzis, A., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2020. Lecture Notes in Computer Science(), vol 12260. Springer, Cham. https://doi.org/10.1007/978-3-030-58219-7_19
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