This paper is in the following e-collection/theme issue:

Digital Health Reviews (1724) Clinical Information and Decision Making (1915) Natural Language Processing (917) Artificial Intelligence (2129) Development and Evaluation of Research Methods, Instruments and Tools (744) Electronic Health Records (1319) mHealth for Data Collection and Research (1196) Ontologies, Classifications, and Coding (324) Clinical Informatics (1325) Machine Learning (2076) Pharmacovigilance (171)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57824, first published .
Applying AI to Structured Real-World Data for Pharmacovigilance Purposes: Scoping Review

Applying AI to Structured Real-World Data for Pharmacovigilance Purposes: Scoping Review

Applying AI to Structured Real-World Data for Pharmacovigilance Purposes: Scoping Review

Authors of this article:

Stella Dimitsaki1 Author Orcid Image ;   Pantelis Natsiavas2 Author Orcid Image ;   Marie-Christine Jaulent1 Author Orcid Image
Article Authors Cited by (11) Tweetations Metrics

Journals

  1. Paithankar V, Devnani D, Nimburkar T. A review article on "AI-guided discovery of novel anti-inflammatory agents for cancer therapy: A new era in drug development". Intelligent Hospital 2025;1(1):100007 View
  2. Rudnisky E, Paudel K. Pharmacovigilance in the Era of Artificial Intelligence: Advancements, Challenges, and Considerations. Cureus 2025 View
  3. Youssef E, Weddle K, Zimmerman L, Palmer D. Pharmacovigilance in Cell and Gene Therapy: Evolving Challenges in Risk Management and Long-Term Follow-Up. Drug Safety 2025 View
  4. Chehab C, Yao X, Heald J, Lathrop S, Hussein H, Michaels M. Opportunities and Challenges in Using Artificial Intelligence in Guideline Development and Implementation. Clinical and Public Health Guidelines 2025;2(4) View
  5. Ferreira-da-Silva R, Cruz-Correia R, Ribeiro I. Beyond black boxes: using explainable causal artificial intelligence to separate signal from noise in pharmacovigilance. International Journal of Clinical Pharmacy 2025 View
  6. Mandaokar D, Bhoyar P, Purohit A. How AI and Machine Learning Stand for Used in Keeping an Eye on Drug Safety a Review Article. International Journal of Innovative Science and Research Technology 2025:2791 View
  7. Bignami E, Russo M, Semeraro F, Bellini V. Balancing Innovation and Control: The European Union AI Act in an Era of Global Uncertainty. JMIR AI 2025;4:e75527 View
  8. Nwokedi V, Odedele M, Yusuff T, Anderson I, Akanbi O, Agu C, Omoike A. Developing and Validating Predictive Models for Adverse Drug Reactions using Electronic Health Records (EHRs): A Narrative Review. Epidemiology and Health Data Insights 2025;1(6):ehdi019 View
  9. Bu W, Wu X, Wang C, Cai Y. Development and validation of a predictive nomogram for severe adverse drug reactions: a dual-center pharmacovigilance study. Frontiers in Pharmacology 2025;16 View
  10. Lu Y, Huang W, Li Y, Xu Y, Wei Q, Sha C, Guo P. Leveraging artificial intelligence in antibody-drug conjugate development: from target identification to clinical translation in oncology. npj Precision Oncology 2025;9(1) View

Books/Policy Documents

  1. Aslam A, Mustafa A, Boota N, Aziz S. Artificial Intelligence in Business. View