Automatic identification of critical follow-up recommendation sentences in radiology reports.

@article{YetisgenYildiz2011AutomaticIO,
  title={Automatic identification of critical follow-up recommendation sentences in radiology reports.},
  author={Meliha Yetisgen-Yildiz and Martin L. Gunn and Fei Xia and Thomas H. Payne},
  journal={AMIA ... Annual Symposium proceedings. AMIA Symposium},
  year={2011},
  volume={2011},
  pages={1593-602}
}
Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. When recommendations are not systematically identified and promptly communicated to referrers, poor patient outcomes can result. Using information technology can improve communication and improve patient safety. In this paper, we describe a text processing approach that uses natural language processing (NLP) and supervised text classification methods to automatically identify… CONTINUE READING

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