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ECSTRA-INSERM @ CLEF eHealth2016-task 2: ICD10 Code Extraction from Death Certificates

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  • معلومة اضافية
    • Contributors:
      Equipe de Recherche en Ingénierie des Connaissances (ERIC); Université Lumière - Lyon 2 (UL2); Université Pierre et Marie Curie - Paris 6 (UPMC); ORS PACA; Biostatistique et épidemiologie clinique; Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM); Entrepôts, Représentation et Ingénierie des Connaissances (ERIC); Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL); Université de Lyon-Université de Lyon; CHU Saint-Antoine AP-HP; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)
    • بيانات النشر:
      CCSD
    • الموضوع:
      2016
    • Collection:
      Université de Lyon: HAL
    • الموضوع:
    • نبذة مختصرة :
      International audience ; This paper describes the participation of ECSTRA-INSERM team at CLEF eHealth 2016, task 2.C. The task involves extracting ICD10 codes from death certificates, mainly described with short plain texts. We cast the task as a machine learning problem involving the prediction of the ICD10 codes (categorical variable) from the raw text transformed into a bag-of-words matrix. We rely on probabilistic topic models that we evaluate against classical classifiers such as SVM and Naive Bayes. We demonstrate the effectiveness of topic models for this task in terms of prediction accuracy and result interpretation.
    • الدخول الالكتروني :
      https://hal.science/hal-02052331
      https://hal.science/hal-02052331v1/document
      https://hal.science/hal-02052331v1/file/16090061.pdf
    • Rights:
      https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.45E5D987