J Biomed Inform - Detecting hedge cues and their scope in biomedical text with conditional random fields.

Tópicos

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Resumo

JECTIVE: Hedging is frequently used in both the biological literature and clinical notes to denote uncertainty or speculation. It is important for text-mining applications to detect hedge cues and their scope; otherwise, uncertain events are incorrectly identified as factual events. However, due to the complexity of language, identifying hedge cues and their scope in a sentence is not a trivial task. Our objective was to develop an algorithm that would automatically detect hedge cues and their scope in biomedical literature.METHODOLOGY: We used conditional random fields (CRFs), a supervised machine-learning algorithm, to train models to detect hedge cue phrases and their scope in biomedical literature. The models were trained on the publicly available BioScope corpus. We evaluated the performance of the CRF models in identifying hedge cue phrases and their scope by calculating recall, precision and F1-score. We compared our models with three competitive baseline systems.RESULTS: Our best CRF-based model performed statistically better than the baseline systems, achieving an F1-score of 88% and 86% in detecting hedge cue phrases and their scope in biological literature and an F1-score of 93% and 90% in detecting hedge cue phrases and their scope in clinical notes.CONCLUSIONS: Our approach is robust, as it can identify hedge cues and their scope in both biological and clinical text. To benefit text-mining applications, our system is publicly available as a Java API and as an online application at http://hedgescope.askhermes.org. To our knowledge, this is the first publicly available system to detect hedge cues and their scope in biomedical literature.

Resumo Limpo

jectiv hedg frequent use biolog literatur clinic note denot uncertainti specul import textmin applic detect hedg cue scope otherwis uncertain event incorrect identifi factual event howev due complex languag identifi hedg cue scope sentenc trivial task object develop algorithm automat detect hedg cue scope biomed literaturemethodolog use condit random field crfs supervis machinelearn algorithm train model detect hedg cue phrase scope biomed literatur model train public avail bioscop corpus evalu perform crf model identifi hedg cue phrase scope calcul recal precis fscore compar model three competit baselin systemsresult best crfbase model perform statist better baselin system achiev fscore detect hedg cue phrase scope biolog literatur fscore detect hedg cue phrase scope clinic notesconclus approach robust can identifi hedg cue scope biolog clinic text benefit textmin applic system public avail java api onlin applic httphedgescopeaskhermesorg knowledg first public avail system detect hedg cue scope biomed literatur

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