Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients.

Journal: Journal of biomedical informatics
Published Date: Jun 1, 2019

Abstract

OBJECTIVE: Clinical care guidelines recommend that newly diagnosed prostate cancer patients at high risk for metastatic spread receive a bone scan prior to treatment and that low risk patients not receive it. The objective was to develop an automated pipeline to interrogate heterogeneous data to evaluate the use of bone scans using a two different Natural Language Processing (NLP) approaches.

Authors

  • Jean Coquet
    Department of Medicine, Stanford University, Stanford, CA, USA.
  • Selen Bozkurt
    Department of Biostatistics and Medical Informatics, Akdeniz University Faculty of Medinice, 48000 Antalya, Turkey.
  • Kathleen M Kan
    Department of Urology, Stanford University School of Medicine, Stanford, USA.
  • Michelle K Ferrari
    Department of Urology, Stanford University School of Medicine, Stanford, USA.
  • Douglas W Blayney
    Stanford University, School of Medicine, Stanford, CA.
  • James D Brooks
    Department of Urology, Stanford School of Medicine, CA.
  • Tina Hernandez-Boussard
    Stanford Center for Biomedical Informatics Research, Stanford, California 94305, USA.

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