The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and risk-benefit profile of medications. With an incidence that has not changed over the last 30 years, ADRs are a significant source of patient morbidity, ...
In 2018, the "Ateliers de Giens" (Giens Workshops) devoted a workshop to artificial intelligence (AI) and led its experts to confirm the potential contribution and theoretical benefit of AI in clinical research, pharmacovigilance, and in improving th...
Journal of chemical information and modeling
Aug 16, 2022
Adverse events are a serious issue in drug development, and many prediction methods using machine learning have been developed. The random split cross-validation is the de facto standard for model building and evaluation in machine learning, but care...
In numerous classification problems, class distribution is not balanced. For example, positive examples are rare in the fields of disease diagnosis and credit card fraud detection. General machine learning methods are known to be suboptimal for such ...
We sought to craft a drug safety signalling pipeline associating latent information in clinical free text with exposures to single drugs and drug pairs. Data arose from 12 secondary and tertiary public hospitals in two Danish regions, comprising appr...
BACKGROUND: The US Food and Drug Administration (FDA) collects and retains several data sets on post-market drugs and associated adverse events (AEs). The FDA Adverse Event Reporting System (FAERS) contains millions of AE reports submitted by the pub...
Drug side effects are closely related to the success and failure of drug development. Here we present a novel machine learning method for side effect prediction. The proposed method treats side effect prediction as a multi-label learning problem and ...
BACKGROUND: Drug-Drug interactions (DDIs) are a challenging problem in drug research. Drug combination therapy is an effective solution to treat diseases, but it can also cause serious side effects. Therefore, DDIs prediction is critical in pharmacol...
In drug development, unexpected side effects are the main reason for the failure of candidate drug trials. Discovering potential side effects of drugsin silicocan improve the success rate of drug screening. However, most previous works extracted and ...