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Cimind: A phonetic-based tool for multilingual named entity recognition in biomedical texts
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In: ISSN: 1532-0464 ; EISSN: 1532-0480 ; Journal of Biomedical Informatics ; https://hal-normandie-univ.archives-ouvertes.fr/hal-02100394 ; Journal of Biomedical Informatics, Elsevier, 2019, pp.103176. ⟨10.1016/j.jbi.2019.103176⟩ (2019)
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Evaluation of the Terminology Coverage in the French Corpus LiSSa.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://hal.archives-ouvertes.fr/hal-01843039 ; Studies in Health Technology and Informatics, IOS Press, 2018, pp.126-130 (2018)
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Formalization of the semantics of iconic languages: An ontology-based method and four semantic-powered applications
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In: ISSN: 0950-7051 ; EISSN: 1872-7409 ; Knowledge-Based Systems ; https://hal.archives-ouvertes.fr/hal-01592749 ; Knowledge-Based Systems, Elsevier, 2017, 135, pp.159 - 179. ⟨10.1016/j.knosys.2017.08.011⟩ (2017)
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SIBM at CLEF eHealth Evaluation Lab 2017: Multilingual Information Extraction with CIM-IND
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In: Conference and Labs of the Evaluation Forum, CLEF 2017 ; https://hal.archives-ouvertes.fr/hal-02102946 ; Conference and Labs of the Evaluation Forum, CLEF 2017, Sep 2017, Dublin, Ireland (2017)
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CIM-IND : Un système multilingue pour l’extraction d’information dans les textes cliniques
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In: 4ème édition du Symposium sur l'Ingénierie de l'Information Médicale, SIIM 2017 ; https://hal.archives-ouvertes.fr/hal-02103551 ; 4ème édition du Symposium sur l'Ingénierie de l'Information Médicale, SIIM 2017, Nov 2017, Toulouse, France (2017)
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Assisting the Translation of SNOMED CT into French.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://hal.inria.fr/hal-00854309 ; Studies in Health Technology and Informatics, IOS Press, 2013, 192, pp.47-51 (2013)
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Validating the semantics of a medical iconic language using ontological reasoning.
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In: ISSN: 1532-0464 ; EISSN: 1532-0480 ; Journal of Biomedical Informatics ; https://hal.inria.fr/hal-00845359 ; Journal of Biomedical Informatics, Elsevier, 2013, 46 (1), pp.56-67. ⟨10.1016/j.jbi.2012.08.006⟩ (2013)
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| 8 |
Validating the semantics of a medical iconic language using ontological reasoning.
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In: ISSN: 1532-0464 ; EISSN: 1532-0480 ; Journal of Biomedical Informatics ; https://hal.archives-ouvertes.fr/hal-00912880 ; Journal of Biomedical Informatics, Elsevier, 2013, 46 (1), pp.56-67. ⟨10.1016/j.jbi.2012.08.006⟩ (2013)
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Matching health information seekers' queries to medical terms
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In: ISSN: 1471-2105 ; BMC Bioinformatics ; https://hal.archives-ouvertes.fr/hal-00845358 ; BMC Bioinformatics, BioMed Central, 2012, 13 Suppl 14, pp.S11. ⟨10.1186/1471-2105-13-S14-S11⟩ (2012)
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Abstract:
International audience ; BACKGROUND: The Internet is a major source of health information but most seekers are not familiar with medical vocabularies. Hence, their searches fail due to bad query formulation. Several methods have been proposed to improve information retrieval: query expansion, syntactic and semantic techniques or knowledge-based methods. However, it would be useful to clean those queries which are misspelled. In this paper, we propose a simple yet efficient method in order to correct misspellings of queries submitted by health information seekers to a medical online search tool. METHODS: In addition to query normalizations and exact phonetic term matching, we tested two approximate string comparators: the similarity score function of Stoilos and the normalized Levenshtein edit distance. We propose here to combine them to increase the number of matched medical terms in French. We first took a sample of query logs to determine the thresholds and processing times. In the second run, at a greater scale we tested different combinations of query normalizations before or after misspelling correction with the retained thresholds in the first run. RESULTS: According to the total number of suggestions (around 163, the number of the first sample of queries), at a threshold comparator score of 0.3, the normalized Levenshtein edit distance gave the highest F-Measure (88.15%) and at a threshold comparator score of 0.7, the Stoilos function gave the highest F-Measure (84.31%). By combining Levenshtein and Stoilos, the highest F-Measure (80.28%) is obtained with 0.2 and 0.7 thresholds respectively. However, queries are composed by several terms that may be combination of medical terms. The process of query normalization and segmentation is thus required. The highest F-Measure (64.18%) is obtained when this process is realized before spelling-correction. CONCLUSIONS: Despite the widely known high performance of the normalized edit distance of Levenshtein, we show in this paper that its combination with the Stoilos algorithm improved the results for misspelling correction of user queries. Accuracy is improved by combining spelling, phoneme-based information and string normalizations and segmentations into medical terms. These encouraging results have enabled the integration of this method into two projects funded by the French National Research Agency-Technologies for Health Care. The first aims to facilitate the coding process of clinical free texts contained in Electronic Health Records and discharge summaries, whereas the second aims at improving information retrieval through Electronic Health Records.
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Keyword:
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]
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URL: https://hal.archives-ouvertes.fr/hal-00845358/document
https://hal.archives-ouvertes.fr/hal-00845358/file/1471-2105-13-S14-S11.pdf
https://doi.org/10.1186/1471-2105-13-S14-S11
https://hal.archives-ouvertes.fr/hal-00845358
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Translating the Foundational Model of Anatomy into French using knowledge-based and lexical methods
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In: ISSN: 1472-6947 ; EISSN: 1472-6947 ; BMC Medical Informatics and Decision Making ; https://hal.archives-ouvertes.fr/hal-00645338 ; BMC Medical Informatics and Decision Making, BioMed Central, 2011, 11 (1), pp.65. ⟨10.1186/1472-6947-11-65⟩ (2011)
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| 11 |
Translating the foundational model of anatomy into french using knowledge-based and lexical methods
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| 12 |
Matching controlled vocabulary words.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://hal.inria.fr/hal-00845377 ; Studies in Health Technology and Informatics, IOS Press, 2003, 95, pp.445-50 (2003)
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