Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies
Not on the map. Why?
Abstract (arXiv)
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 seeking to resort to NLP to monitor these outlets. We propose for the first time the use of the SpanBERT architecture for the task of ADE extraction: this new version of the popular BERT transformer showed improved capabilities with multi-token text spans. We validate our hypothesis with experiments on two datasets (SMM4H and CADEC) with different text typologies (tweets and blog posts), finding that SpanBERT combined with a CRF outperforms all the competitors on both of them.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 8 of its 25 references that are in the map. First posted on arXiv 19 May 2021.
Builds on
8 of 25 references.
References · 8
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,947
- 2016Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translationcited by 1,475
- 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 834
- 2019Span-based Joint Entity and Relation Extraction with Transformer Pre-trainingcited by 133
- 2020An Effective Transition-based Model for Discontinuous NERcited by 33
- 2020Dissecting Span Identification Tasks with Performance Predictioncited by 13
- 2018Neural DrugNetcited by 1
Built on by
Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 2; 2025: 1.
7 papers.
- 2021Exploring a Unified Sequence-To-Sequence Transformer for Medical Product Safety Monitoring in Social Mediacited by 9
- 2021NADE: A Benchmark for Robust Adverse Drug Events Extraction in Face of Negationscited by 5
- 2022Increasing Adverse Drug Events extraction robustness on social media: case study on negation and speculationcited by 3
- 2022AILAB-Udine@SMM4H 22: Limits of Transformers and BERT Ensemblescited by 2
- 2024MultiADE: A Multi-domain Benchmark for Adverse Drug Event Extractioncited by 1
- 2024DistALANER: Distantly Supervised Active Learning Augmented Named Entity Recognition in the Open Source Software Ecosystemcited by 0
- 2025RA-MTR: A Retrieval Augmented Multi-Task Reader based Approach for Inspirational Quote Extraction from Long Documentscited by 0
- 2025RA-MTR: A Retrieval Augmented Multi-Task Reader based Approach for Inspirational Quote Extraction from Long Documents17 Feb 2025
- 2024MultiADE: A Multi-domain Benchmark for Adverse Drug Event Extraction28 May 2024
- 2024DistALANER: Distantly Supervised Active Learning Augmented Named Entity Recognition in the Open Source Software Ecosystem25 Feb 2024
- 2022AILAB-Udine@SMM4H 22: Limits of Transformers and BERT Ensembles7 Sep 2022
- 2022Increasing Adverse Drug Events extraction robustness on social media: case study on negation and speculation6 Sep 2022
- 2021NADE: A Benchmark for Robust Adverse Drug Events Extraction in Face of Negations21 Sep 2021
- 2021Exploring a Unified Sequence-To-Sequence Transformer for Medical Product Safety Monitoring in Social Media13 Sep 2021