Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods.

@article{Patel2017CorrelatingMA,
  title={Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods.},
  author={Tejal A. Patel and Mamta Puppala and Richard Ogunti and Joe Ensor and Tiancheng He and Jitesh B Shewale and Donna P. Ankerst and Virginia G. Kaklamani and Angel A. Rodriguez and Stephen T. C. Wong and Jenny C. Chang},
  journal={Cancer},
  year={2017},
  volume={123 1},
  pages={114-121}
}
BACKGROUND A key challenge to mining electronic health records for mammography research is the preponderance of unstructured narrative text, which strikingly limits usable output. The imaging characteristics of breast cancer subtypes have been described previously, but without standardization of parameters for data mining. METHODS The authors searched the enterprise-wide data warehouse at the Houston Methodist Hospital, the Methodist Environment for Translational Enhancement and Outcomes… CONTINUE READING
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