Autonomous detection, grading, and reporting of postoperative complications using natural language processing.

Journal: Surgery
Published Date: Dec 1, 2018

Abstract

INTRODUCTION: Natural language processing, a computer science technique that allows interpretation of narrative text, is infrequently used to identify surgical complications. We designed a natural language processing algorithm to identify and grade the severity of deep venous thrombosis and pulmonary embolism (together: venous thromboembolism).

Authors

  • Luke V Selby
    Department of Surgery, Memorial Sloan Kettering Cancer Center.
  • Wazim R Narain
    Department of Surgery Health Informatics, Memorial Sloan Kettering Cancer Center.
  • Ashley Russo
    Department of Surgery, Memorial Sloan Kettering Cancer Center.
  • Vivian E Strong
    Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, H-1217, New York, NY 10065, USA. Electronic address: strongv@mskcc.org.
  • Peter Stetson
    Memorial Sloan Kettering Cancer Center, New York, NY 10065, United States.

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