Navigating the Complexities of Artificial Intelligence-Enabled Real-World Data Collection for Oncology Pharmacovigilance.

Journal: JCO clinical cancer informatics
PMID: 38713889

Abstract

This new editorial discusses the promise and challenges of successful integration of natural language processing methods into electronic health records for timely, robust, and fair oncology pharmacovigilance.

Authors

  • Jack Gallifant
    Centre for Human and Applied Physiological Sciences, School of Basic and Medical Biosciences, King's College London, London, UK. Electronic address: jack.gallifant@kcl.ac.uk.
  • Leo Anthony Celi
    Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Elad Sharon
    Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada, The Hebrew University of Jerusalem, 9112001, Jerusalem, Israel.
  • Danielle S Bitterman
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.

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