Abstract Biomedical Entity Linking (BEL) is the task of map** of spans of text within
biomedical documents to normalized, unique identifiers within an ontology. This is an …

With the rapid development of artificial intelligence (AI) technologies, and the large amount
of pharmacovigilance-related data stored in an electronic manner, data-driven automatic …

The number of users of social media continues to grow, with nearly half of adults worldwide
and two-thirds of all American adults using social networking. Advances in automated data …

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 …

Importance Automatic curation of consumer-generated, opioid-related social media big data
may enable real-time monitoring of the opioid epidemic in the United States. Objective To …

Objective: We present a narrative review of recent work on the utilisation of Natural
Language Processing (NLP) for the analysis of social media (including online health …

Objective The aim of the Social Media Mining for Health Applications (# SMM4H) shared
tasks is to take a community-driven approach to address the natural language processing …

Objective Research on pharmacovigilance from social media data has focused on mining
adverse drug events (ADEs) using annotated datasets, with publications generally focusing …

Background There is a lack of research studying patient-generated data on Reddit, one of
the world's most popular forums with active users interested in dermatology. Techniques …

Objective Medical concept normalization (MCN), the task of linking textual mentions to
concepts in an ontology, provides a solution to unify different ways of referring to the same …