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Overview of the CLEF eHealth Evaluation Lab 2015

  • Lorraine Goeuriot
  • Liadh Kelly
  • Hanna Suominen
  • Leif Hanlen
  • Aurélie Névéol
  • Cyril Grouin
  • João Palotti
  • Guido Zuccon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9283)

Abstract

This paper reports on the 3rd CLEFeHealth evaluation lab, which continues our evaluation resource building activities for the medical domain. In this edition of the lab, we focus on easing patients and nurses in authoring, understanding, and accessing eHealth information. The 2015 CLEFeHealth evaluation lab was structured into two tasks, focusing on evaluating methods for information extraction (IE) and information retrieval (IR). The IE task introduced two new challenges. Task 1a focused on clinical speech recognition of nursing handover notes; Task 1b focused on clinical named entity recognition in languages other than English, specifically French. Task 2 focused on the retrieval of health information to answer queries issued by general consumers seeking information to understand their health symptoms or conditions.

The number of teams registering their interest was 47 in Tasks 1 (2 teams in Task 1a and 7 teams in Task 1b) and 53 in Task 2 (12 teams) for a total of 20 unique teams. The best system recognized 4, 984 out of 6, 818 test words correctly and generated 2, 626 incorrect words (i.e., \(38.5 \%\) error) in Task 1a; had the F-measure of 0.756 for plain entity recognition, 0.711 for normalized entity recognition, and 0.872 for entity normalization in Task 1b; and resulted in P@10 of 0.5394 and nDCG@10 of 0.5086 in Task 2. These results demonstrate the substantial community interest and capabilities of these systems in addressing challenges faced by patients and nurses. As in previous years, the organizers have made data and tools available for future research and development.

Keywords

Evaluation Information retrieval Information extraction Medical informatics Nursing records Patient handoff/handover Speech recognition Test-set generation Text classification Text segmentation Self-diagnosis 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lorraine Goeuriot
    • 1
  • Liadh Kelly
    • 2
  • Hanna Suominen
    • 3
    • 4
    • 5
    • 6
  • Leif Hanlen
    • 3
    • 4
    • 5
  • Aurélie Névéol
    • 7
  • Cyril Grouin
    • 7
  • João Palotti
    • 8
  • Guido Zuccon
    • 9
  1. 1.LIGUniversité Grenoble AlpesGrenobleFrance
  2. 2.ADAPT CentreTrinity CollegeDublinIreland
  3. 3.NICTACanberraAustralia
  4. 4.The Australian National UniversityCanberraAustralia
  5. 5.University of CanberraCanberraAustralia
  6. 6.University of TurkuTurkuFinland
  7. 7.LIMSI CNRS UPR 3251OrsayFrance
  8. 8.Vienna University of TechnologyViennaAustria
  9. 9.Queensland University of TechnologyBrisbaneAustralia

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