The advances achieved in Natural Language Processing make it possible to automatically
mine information from electronically created documents. Many Natural Language …

Objective: To tackle the extraction of adverse drug reaction events in electronic health
records. The challenge stands in inferring a robust prediction model from highly unbalanced …

A significant amount of information about drug-related safety issues such as adverse effects
are published in medical case reports that can only be explored by human readers due to …

Abstract CSIRO Adverse Drug Event Corpus (C adec) is a new rich annotated corpus of
medical forum posts on patient-reported Adverse Drug Events (ADEs). The corpus is …

Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its
input will, however, only be optimized if systems can manage to deal with its tremendous …

With the rapidly growing use of electronic health records, the possibility of large-scale
clinical information extraction has drawn much attention. We aim to extract adverse drug …

Background Many biomedical relation extraction systems are machine-learning based and
have to be trained on large annotated corpora that are expensive and cumbersome to …

Introduction Adverse drug reaction reports are usually manually assessed by
pharmacovigilance experts to detect safety signals associated with drugs. With the recent …

Objective Drugs have tremendous potential to cure and relieve disease, but the risk of
unintended effects is always present. Healthcare providers increasingly record data in …

Abstract “Psychiatric Treatment Adverse Reactions”(PsyTAR) corpus is an annotated corpus
that has been developed using patients narrative data for psychiatric medications …