Abstract Objective Automatic monitoring of Adverse Drug Reactions (ADRs), defined as
adverse patient outcomes caused by medications, is a challenging research problem that is …

Natural language processing (NLP) is a form of machine learning which enables the
processing and analysis of free text. When used with medical notes, it can aid in the …

Efficient access to chemical information contained in scientific literature, patents, technical
reports, or the web is a pressing need shared by researchers and patent attorneys from …

The simultaneous administration of multiple drugs increases the probability of interaction
among them, as one drug may affect the activities of others. This interaction among drugs …

Background The medical subdomain of a clinical note, such as cardiology or neurology, is
useful content-derived metadata for develo** machine learning downstream applications …

Identification of adverse drug reactions (ADRs) during the post-marketing phase is one of
the most important goals of drug safety surveillance. Spontaneous reporting systems (SRS) …

The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug
events (ADEs) with pharmaceutical products. This article is a comprehensive structured …

Big data methodologies, made possible with the increasing generation and availability of
digital data and enhanced analytical capabilities, have produced new insights to improve …

Background Prescription medication (PM) misuse/abuse has emerged as a national crisis in
the United States, and social media has been suggested as a potential resource for …

Objective This article presents our approaches to extraction of medications and associated
adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 …