37 citations · 57 across the 9 of their papers we have counts for
4 papers · 1 filter
Increasing Adverse Drug Events extraction robustness on social media: case study on negation and speculation
Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni +2
In the last decade, an increasing number of users have started reporting Adverse Drug Events (ADE) on social media platforms, blogs, and health forums. Given the large volume of re…
NADE: A Benchmark for Robust Adverse Drug Events Extraction in Face of Negations
Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni +2
Adverse Drug Event (ADE) extraction models can rapidly examine large collections of social media texts, detecting mentions of drug-related adverse reactions and trigger medical inv…
Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies
Beatrice Portelli, Daniele Passabì, Edoardo Lenzi +3
In recent years, Internet users are reporting Adverse Drug Events (ADE) on social media, blogs and health forums. Because of the large volume of reports, pharmacovigilance is seeki…
Predicting the Usefulness of Amazon Reviews Using Off-The-Shelf Argumentation Mining
Marco Passon, Marco Lippi, Giuseppe Serra +1
Internet users generate content at unprecedented rates. Building intelligent systems capable of discriminating useful content within this ocean of information is thus becoming a ur…