no code implementations • SMM4H (COLING) 2022 • Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
This paper describes the models developed by the AILAB-Udine team for the SMM4H’22 Shared Task.
no code implementations • 31 Jul 2023 • François Remy, Simone Scaboro, Beatrice Portelli
Biomedical entity linking, also known as biomedical concept normalization, has recently witnessed the rise to prominence of zero-shot contrastive models.
1 code implementation • 8 Jun 2023 • Simone Scaboro, Beatrice Portellia, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
Adverse Event (ADE) extraction is one of the core tasks in digital pharmacovigilance, especially when applied to informal texts.
1 code implementation • 21 Oct 2022 • Beatrice Portelli, Simone Scaboro, Enrico Santus, Hooman Sedghamiz, Emmanuele Chersoni, Giuseppe Serra
Medical term normalization consists in mapping a piece of text to a large number of output classes.
no code implementations • 7 Sep 2022 • Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
This paper describes the models developed by the AILAB-Udine team for the SMM4H 22 Shared Task.
no code implementations • 6 Sep 2022 • Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
In the last decade, an increasing number of users have started reporting Adverse Drug Events (ADE) on social media platforms, blogs, and health forums.
1 code implementation • WNUT (ACL) 2021 • Simone Scaboro, Beatrice Portelli, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra
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 investigations.