Clinical language search algorithm from free-text: facilitating appropriate imaging.

Journal: BMC medical imaging
Published Date: Feb 4, 2022

Abstract

BACKGROUND: The comprehensiveness and maintenance of the American College of Radiology (ACR) Appropriateness Criteria (AC) makes it a unique resource for evidence-based clinical imaging decision support, but it is underutilized by clinicians. To facilitate the use of imaging recommendations, we develop a natural language processing (NLP) search algorithm that automatically matches clinical indications that physicians write into imaging orders to appropriate AC imaging recommendations.

Authors

  • Gunvant R Chaudhari
    University of California San Francisco (UCSF), Radiology and Biomedical Imaging, 505 Parnassus Ave, San Francisco, CA 94143, USA.
  • Yeshwant R Chillakuru
    University of California San Francisco (UCSF), Radiology and Biomedical Imaging, 505 Parnassus Ave, San Francisco, CA 94143, USA; George Washington School Medicine and Health Sciences, 2300 I St NW, Washington, DC 20052, USA.
  • Timothy L Chen
    University of California San Francisco (UCSF), Radiology and Biomedical Imaging, 505 Parnassus Ave, San Francisco, CA 94143, USA; University of Illinois College of Medicine, 1853 W Polk St, Chicago, IL 60612, USA.
  • Valentina Pedoia
    Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.
  • Thienkhai H Vu
    University of California San Francisco (UCSF), Radiology and Biomedical Imaging, 505 Parnassus Ave, San Francisco, CA 94143, USA.
  • Christopher P Hess
    Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA; Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
  • Youngho Seo
    Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
  • Jae Ho Sohn
    Radiology & Biomedical Imaging, UCSF Medical Center, 505 Parnassus Ave, San Francisco, CA, 94158, USA. sohn87@gmail.com.

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