Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.

Journal: Drug safety
PMID: 39786481

Abstract

BACKGROUND: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence of their real-world effectiveness remains unclear.

Authors

  • Su Golder
    Department of Health Sciences, University of York, York, United Kingdom.
  • Dongfang Xu
  • Karen O'Connor
    Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ, USA.
  • Yunwen Wang
    Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, California, USA.
  • Mahak Batra
    Department of Health Sciences, University of York, York, YO10 5DD, UK.
  • Graciela Gonzalez Hernandez
    Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Keywords

External Resources

Popular Topics
Recent Journals