Using automatically extracted information from mammography reports for decision-support.

Journal: Journal of biomedical informatics
Published Date: Jul 4, 2016

Abstract

OBJECTIVE: To evaluate a system we developed that connects natural language processing (NLP) for information extraction from narrative text mammography reports with a Bayesian network for decision-support about breast cancer diagnosis. The ultimate goal of this system is to provide decision support as part of the workflow of producing the radiology report.

Authors

  • Selen Bozkurt
    Department of Biostatistics and Medical Informatics, Akdeniz University Faculty of Medinice, 48000 Antalya, Turkey.
  • Francisco Gimenez
    Department of Radiology and Medicine (Biomedical Informatics Research), Stanford University, Richard M. Lucas Center, 1201 Welch Road, Office P285, Stanford, CA 94305-5488, United States.
  • Elizabeth S Burnside
    Department of Radiology, University of Wisconsin, Madison, WI, United States.
  • Kemal H Gulkesen
    Akdeniz University Faculty of Medicine, Department of Biostatistics and Medical Informatics, Antalya, Turkey.
  • Daniel L Rubin
    Department of Biomedical Data Science, Stanford University School of Medicine Medical School Office Building, Stanford CA 94305-5479.

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