J Am Med Inform Assoc - Named entity recognition of follow-up and time information in 20,000 radiology reports.

Tópicos

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Resumo

JECTIVE: To develop a system to extract follow-up information from radiology reports. The method may be used as a component in a system which automatically generates follow-up information in a timely fashion.METHODS: A novel method of combining an LSP (labeled sequential pattern) classifier with a CRF (conditional random field) recognizer was devised. The LSP classifier filters out irrelevant sentences, while the CRF recognizer extracts follow-up and time phrases from candidate sentences presented by the LSP classifier.MEASUREMENTS: The standard performance metrics of precision (P), recall (R), and F measure (F) in the exact and inexact matching settings were used for evaluation.RESULTS: Four experiments conducted using 20,000 radiology reports showed that the CRF recognizer achieved high performance without time-consuming feature engineering and that the LSP classifier further improved the performance of the CRF recognizer. The performance of the current system is P=0.90, R=0.86, F=0.88 in the exact matching setting and P=0.98, R=0.93, F=0.95 in the inexact matching setting.CONCLUSION: The experiments demonstrate that the system performs far better than a baseline rule-based system and is worth considering for deployment trials in an alert generation system. The LSP classifier successfully compensated for the inherent weakness of CRF, that is, its inability to use global information.

Resumo Limpo

jectiv develop system extract followup inform radiolog report method may use compon system automat generat followup inform time fashionmethod novel method combin lsp label sequenti pattern classifi crf condit random field recogn devis lsp classifi filter irrelev sentenc crf recogn extract followup time phrase candid sentenc present lsp classifiermeasur standard perform metric precis p recal r f measur f exact inexact match set use evaluationresult four experi conduct use radiolog report show crf recogn achiev high perform without timeconsum featur engin lsp classifi improv perform crf recogn perform current system p r f exact match set p r f inexact match settingconclus experi demonstr system perform far better baselin rulebas system worth consid deploy trial alert generat system lsp classifi success compens inher weak crf inabl use global inform

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