Machine Learning and Rule-based Approaches to Assertion Classification

Machine Learning and Rule-based Approaches to Assertion Classification

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 asserti...

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Bibliographic Details
Main Authors: Uzuner, Ozlem, Zhang, Xiaoran, Sibanda, Tawanda
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: BMJ Publishing Group 2010
Online Access:http://hdl.handle.net/1721.1/52450
https://orcid.org/0000-0001-8011-9850

Internet

http://hdl.handle.net/1721.1/52450
https://orcid.org/0000-0001-8011-9850

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