# Enhancing Pharmacovigilance with Drug Reviews and Social Media

arXiv: https://arxiv.org/abs/2004.08731 · HTML: https://mlsanity.com/paper/2004.08731/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Apr 2020.

## Built on by (most cited first, 2 of 2)

- [Fine-Tuning BERT for Automatic ADME Semantic Labeling in FDA Drug Labeling to Enhance Product-Specific Guidance Assessment](https://mlsanity.com/paper/2207.12376/) (2022)
- [Deep Learning Models in Detection of Dietary Supplement Adverse Event Signals from Twitter](https://mlsanity.com/paper/2106.11403/) (2021)

## Abstract (arXiv)

This paper explores whether the use of drug reviews and social media could be leveraged as potential alternative sources for pharmacovigilance of adverse drug reactions (ADRs). We examined the performance of BERT alongside two variants that are trained on biomedical papers, BioBERT7, and clinical notes, Clinical BERT8. A variety of 8 different BERT models were fine-tuned and compared across three different tasks in order to evaluate their relative performance to one another in the ADR tasks. The tasks include sentiment classification of drug reviews, presence of ADR in twitter postings, and named entity recognition of ADRs in twitter postings. BERT demonstrates its flexibility with high performance across all three different pharmacovigilance related tasks.