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Lessons Learned from the Usability Evaluation of a Simulated Patient Dialogue System
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In: ISSN: 0148-5598 ; EISSN: 1573-689X ; Journal of Medical Systems ; https://hal.archives-ouvertes.fr/hal-03452553 ; Journal of Medical Systems, Springer Verlag (Germany), 2021, 45 (7), ⟨10.1007/s10916-021-01737-4⟩ (2021)
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A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine
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A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine
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In: BMC Med Inform Decis Mak (2021)
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Designing a virtual patient dialogue system based on terminology-rich resources: Challenges and evaluation
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Designing a virtual patient dialogue system based on terminology-rich resources: challenges and evaluation
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In: ISSN: 1351-3249 ; EISSN: 1469-8110 ; Natural Language Engineering ; https://hal.archives-ouvertes.fr/hal-02358021 ; Natural Language Engineering, Cambridge University Press (CUP), 2019, pp.1-38 (2019)
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Biomedical Term Extraction: NLP Techniques in Computational Medicine
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Abstract:
Artificial Intelligence (AI) and its branch Natural Language Processing (NLP) in particular are main contributors to recent advances in classifying documentation and extracting information from assorted fields, Medicine being one that has gathered a lot of attention due to the amount of information generated in public professional journals and other means of communication within the medical profession. The typical information extraction task from technical texts is performed via an automatic term recognition extractor. Automatic Term Recognition (ATR) from technical texts is applied for the identification of key concepts for information retrieval and, secondarily, for machine translation. Term recognition depends on the subject domain and the lexical patterns of a given language, in our case, Spanish, Arabic and Japanese. In this article, we present the methods and techniques for creating a biomedical corpus of validated terms, with several tools for optimal exploitation of the information therewith contained in said corpus. This paper also shows how these techniques and tools have been used in a prototype.
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Keyword:
Biomedical Terminology; Informática; Information Extraction; Natural Language Processing; Term Recognition
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URL: https://doi.org/10.9781/ijimai.2018.04.001
http://hdl.handle.net/10486/688968
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Biomedical Term Extraction: NLP Techniques in Computational Medicine
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Collecting and POS-tagging a lexical resource of Japanese biomedical terms from a corpus ; Recogida y etiquetado morfológico de un lexicón de términos biomédicos en japonés a partir de corpus
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Errores léxicos en el español oral no nativo: análisis de la interlengua basado en corpus ; Lexical errors in non-native oral Spanish: a corpus-based error analysis
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Campillos Llanos, Leonardo. - : Universidad de Alicante. Departamento de Filología Española, Lingüística General y Teoría de la Literatura, 2014
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Collecting and POS-tagging a lexical resource of Japanese biomedical terms from a corpus ; Recogida y etiquetado morfológico de un lexicón de términos biomédicos en japonés a partir de corpus
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