Detection of Patient-Level Immunotherapy-Related Adverse Events (irAEs) from Clinical Narratives of Electronic Health Records: A High-Sensitivity Artificial Intelligence Model.

Journal: Pragmatic and observational research
Published Date: Dec 20, 2024

Abstract

PURPOSE: We developed an artificial intelligence (AI) model to detect immunotherapy -related adverse events (irAEs) from clinical narratives of electronic health records (EHRs) at the patient level.

Authors

  • Md Muntasir Zitu
    Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
  • Margaret E Gatti-Mays
    Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH, 43210, USA.
  • Kai C Johnson
    Division of Medical Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH, 43210, USA.
  • Shijun Zhang
    Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
  • Aditi Shendre
    Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
  • Mohamed I Elsaid
    Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
  • Lang Li
    Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.

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