Machine Learning and Rule-based Approaches to Assertion Classification

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Uzuner O., Zhang X., Sibanda T.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, vol.16, no.1, pp.109-115, 2009 (SCI-Expanded) identifier identifier identifier


Objectives: The authors study two approaches to assertion classification. One of these approaches, Extended NegEx (ENegEx), extends the rule-based NegEx algorithm to cover alter-association assertions; the other, Statistical Assertion Classifier (StAC), presents a machine learning solution to assertion classification.