Machine learning in drug safety: exploring applications and addressing challenges for improved patient safety

  • Riya Jose Rajiv Gandhi University of health sciences
Keywords: Artificial intelligence, Machine Learning, Pharmacovigilance, Drug safety, Applications

Abstract

Artificial intelligence (AI) has emerged as a powerful tool in the pharmaceutical industry, utilizing machine learning and natural language processing to access and analyze vast amounts of research and information. AI has a wide range of applications in the field of pharmacovigilance (PV) and drug safety, including the improvement of information retrieval, the identification of medical concepts, text translation, automated illness image classification, and the gathering of adverse drug response (ADR) data. This review article explores the potential of AI in drug safety and its challenges, highlighting its applications along with examples. By embracing AI advancements, the industry can enhance drug safety monitoring, improve data analysis, and contribute to better healthcare outcomes. 

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References

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Published
2023-09-01
How to Cite
1.
Jose R. Machine learning in drug safety: exploring applications and addressing challenges for improved patient safety. jpadr [Internet]. 2023Sep.1 [cited 2024Nov.6];4(3):6-12. Available from: https://jpadr.com/index.php/jpadr/article/view/139