Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante) · 2019 · 11 citations · 7 references
ComputingComputer ScienceHealth InformaticsBiomedical Text MiningKnowledge RepresentationNatural Language ProcessingClinical Natural Language ProcessingDisease Mention DetectionHealth Information RetrievalInformation ExtractionNamed Entity RecognitionSemantic NetworksCross-domain Disease Mention DetectionCross-domain GeneralizationCross-domain MappingDisease Entity RecognitionEntity-aware RetrievalHealthcare Knowledge RepresentationKnowledge Discovery ProcessesNatural Language Inference
This paper summarises the results of the third edition of the eHealth Knowledge Discovery (KD) challenge, hosted at the Iberian Language Evaluation Forum 2020. The eHealth-KD challenge proposes two computational tasks involving the identification of semantic entities and relations in natural language text, focusing on Spanish language health documents. In this edition, besides text extracted from medical sources, Wikipedia content was introduced into the corpus, and a novel transfer-learning evaluation scenario was designed that challenges participants to create systems that provide cross-domain generalisation. A total of eight teams participated with a variety of approaches including deep learning end-to-end systems as well as rule-based and knowledge-driven techniques. This paper analyses the most successful approaches and highlights the most interesting challenges for future research in this field.
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