Publication | Closed Access
Retrieving Medical Records with "sennamed": NEC Labs America at TREC 2012 Medical Record Track.
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2012
Year
Unknown Venue
EngineeringIntelligent Information RetrievalDiagnosisMedical Records TrackCorpus LinguisticsText MiningNatural Language ProcessingNec Laboratories AmericaAutomatic Retrieval RunsInformation RetrievalData ScienceData MiningDocument ClassificationNec Labs AmericaBiomedical Text MiningClinical DatabaseMedical Record TrackKnowledge RetrievalKnowledge DiscoveryElectronic Health RecordMedical RecordsBusinessMedicineTest CollectionHealth Informatics
Abstract : In this notebook, we describe the automatic retrieval runs from NEC Laboratories America (NECLA) for the Text REtrieval Conference (TREC) 2012 Medical Records track. Our approach is based on a combination of UMLS medical concept detection and a set of simple retrieval models. Our best run, sennamed2, has achieved the best inferred average precision (infAP) score on 5 of the 47 test topics, and obtained a higher score than the median of all submission runs on 27 other topics. Overall, sennamed2 ranks at the second place amongst all the 82 automatic runs submitted for this track, and obtains the third place amongst both automatic and manual submissions.
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