Artificial intelligence (AI) in pharmacovigilance: A systematic review on predicting adverse drug reactions (ADR) in hospitalized patients.

Journal: Research in social & administrative pharmacy : RSAP
PMID: 39961738

Abstract

INTRODUCTION: Adverse drug reactions (ADRs) significantly impact healthcare systems, leading to increased hospitalization rates and costs. With the growing adoption of artificial intelligence (AI) in healthcare, machine learning (ML) models offer promising solutions for ADR prediction. However, comprehensive evaluations of these models remain limited.

Authors

  • Viola Savy Dsouza
    Faculty of Health, Medicine, and Life Sciences (FHML), Maastricht University, Maastricht, the Netherlands. Electronic address: violadsouza1995@gmail.com.
  • Lada Leyens
    Centre for Regulatory Science, Department of Health Information, Prasanna School of Public Health, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India.
  • Jestina Rachel Kurian
    Department of Data Science, Prasanna School of Public Health, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India.
  • Angela Brand
    United Nations University-Maastricht Economic and Social Research Institute on Innovation and Technology, Maastricht, The Netherlands.
  • Helmut Brand
    Department of International Health, Faculty of Health Medicine and Life Sciences, Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands.

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