First author

Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records

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 …

Using machine learning to identify patients at high risk of inappropriate drug dosing in periods with renal dysfunction

**Purpose**: Dosing of renally cleared drugs in patients with kidney failure often deviates from clinical guidelines, so we sought to elicit predictors of receiving inappropriate doses of renal risk drugs. **Patients and methods**: We combined data …

Drug interactions in hospital prescriptions in Denmark: Prevalence and associations with adverse outcomes

**Purpose** While the beneficial effects of medications are numerous, drug–drug interactions may lead to adverse drug reactions that are preventable causes of morbidity and mortality. Our goal was to quantify the prevalence of potential drug–drug …