The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug
events (ADEs) with pharmaceutical products. This article is a comprehensive structured …

To reduce adverse drug events (ADEs), hospitals need a system to support them in
monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing …

Large-scale drug safety surveillance and pharmacovigilance are key components of
effective drug regulation systems, clinical practice, and public health programs [1]. Although …

The primary goal of drug safety researchers and regulators is to promptly identify adverse
drug reactions. Doing so may in turn prevent or reduce the harm to patients and ultimately …

Objective The primary objective of this review is to investigate the effectiveness of machine
learning and deep learning methodologies in the context of extracting adverse drug events …

Developed by OpenAI, ChatGPT is a sophisticated large language model (LLM) capable of
generating responses that resemble human language when presented with written prompts …

Introduction This work describes the Medication and Adverse Drug Events from Electronic
Health Records (MADE 1.0) corpus and provides an overview of the MADE 1.0 2018 …

Objective: It is vital to detect the full safety profile of a drug throughout its market life. Current
pharmacovigilance systems still have substantial limitations, however. The objective of our …

The safety of medication use has been a priority in the United States since the late 1930s.
Recently, it has gained prominence due to the increasing amount of data suggesting that a …

Introduction Early detection of adverse drug events (ADEs) from electronic health records is
an important, challenging task to support pharmacovigilance and drug safety surveillance. A …