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 …
H Wang, YJ Ding, Y Luo - Drug safety, 2023 - Springer
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 …
X Wang, G Hripcsak, M Markatou… - Journal of the American …, 2009 - academic.oup.com
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 …
A Wong, JM Plasek, SP Montecalvo… - … : The Journal of Human …, 2018 - Wiley Online Library
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 …