Automated Identification of Patients With Immune-Related Adverse Events From Clinical Notes Using Word Embedding and Machine Learning.

Journal: JCO clinical cancer informatics
Published Date: May 1, 2021

Abstract

PURPOSE: Although immune checkpoint inhibitors (ICIs) have substantially improved survival in patients with advanced malignancies, they are associated with a unique spectrum of side effects termed immune-related adverse events (irAEs). To ensure treatment safety, research efforts are needed to comprehensively detect and understand irAEs. Retrospective analysis of data from electronic health records can provide knowledge to characterize these toxicities. However, such information is not captured in a structured format within the electronic health record and requires manual chart review.

Authors

  • Samir Gupta
    Department of Computer and Information Sciences, University of Delaware, Newark, DE, 19711, USA. sgupta@udel.edu.
  • Anas Belouali
    Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC.
  • Neil J Shah
    Memorial Sloan Kettering Cancer Center, Manhattan, New York, NY.
  • Michael B Atkins
    Lombardi Comprehensive Cancer Center, MedStar Georgetown University Hospital, Washington, DC.
  • Subha Madhavan
    Innovation Center For Biomedical Informatics, Georgetown University, Washington D.C, United States of America.

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