Publication | Open Access
Answering clinical questions with role identification
56
Citations
19
References
2003
Year
Unknown Venue
EngineeringClinical QuestionsCorpus LinguisticsText MiningNatural Language ProcessingInformation RetrievalMedical Expert SystemComputational LinguisticsPico FormatMedical Question-answeringLanguage StudiesBiomedical Text MiningMachine TranslationHealth InformaticsQuestion AnsweringNatural Language InterfaceNlp TaskClinical DataNursingPatient EducationClinical PracticeLinguisticsNatural Language Analysis
We describe our work in progress on natural language analysis in medical question-answering in the context of a broader medical text-retrieval project. We analyze the limitations in the medical domain of the technologies that have been developed for general question-answering systems, and describe an alternative approach whose organizing principle is the identification of semantic roles in both question and answer texts that correspond to the fields of PICO format.
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