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Augmenting Electronic Health Records for Adverse Event Detection
2026-02-11
health informatics
Title + abstract only
View on medRxiv
Show abstract
ObjectiveAdverse events (AEs) resulting from medical interventions are significant contributors to patient morbidity, mortality, and healthcare costs. Prediction of these events using electronic health records (EHRs) can facilitate timely clinical interventions. However, effective prediction remains challenging due to severe class imbalance, missing labels, and the complexity of EHR records. Classical machine learning approaches frequently underperform due to insufficient representation of minor...
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Journal of Biomedical Informatics
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