A Web Application for Adrenal Incidentaloma Identification, Tracking, and Management Using Machine Learning.

Journal: Applied clinical informatics
Published Date:

Abstract

BACKGROUND: Incidental radiographic findings, such as adrenal nodules, are commonly identified in imaging studies and documented in radiology reports. However, patients with such findings frequently do not receive appropriate follow-up, partially due to the lack of tools for the management of such findings and the time required to maintain up-to-date lists. Natural language processing (NLP) is capable of extracting information from free-text clinical documents and could provide the basis for software solutions that do not require changes to clinical workflows.

Authors

  • Wasif Bala
    Boston University School of Medicine, Boston, MA 02215, United States.
  • Jackson Steinkamp
    Boston Medical Center, One Boston Medical Center Pl, Boston, Massachusetts, United States.
  • Timothy Feeney
    Boston Medical Center, One Boston Medical Center Pl, Boston, Massachusetts, United States.
  • Avneesh Gupta
    Boston Medical Center, One Boston Medical Center Pl, Boston, Massachusetts, United States.
  • Abhinav Sharma
    Department of Biological Sciences and Bioengineering (BSBE), IIT, Kanpur, India.
  • Jake Kantrowitz
    Department of Internal Medicine, Kent Hospital, Brown University Alpert Medical School, Warwick, Rhode Island, United States.
  • Nicholas Cordella
    Boston Medical Center, One Boston Medical Center Pl, Boston, Massachusetts, United States.
  • James Moses
    Boston Medical Center, One Boston Medical Center Pl, Boston, Massachusetts, United States.
  • Frederick Thurston Drake
    Boston Medical Center, One Boston Medical Center Pl, Boston, Massachusetts, United States.