DrugWatch: A Comprehensive Multi-Source Data Visualisation Platform for Drug Safety Information
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Abstract (arXiv)
Drug safety research is crucial for maintaining public health, often requiring comprehensive data support. However, the resources currently available to the public are limited and fail to provide a comprehensive understanding of the relationship between drugs and their side effects. This paper introduces DrugWatch, an easy-to-use and interactive multi-source information visualisation platform for drug safety study. It allows users to understand common side effects of drugs and their statistical information, flexibly retrieve relevant medical reports, or annotate their own medical texts with our automated annotation tool. Supported by NLP technology and enriched with interactive visual components, we are committed to providing researchers and practitioners with a one-stop information analysis, retrieval, and annotation service. The demonstration video is available at https://www.youtube.com/watch?v=RTqDgxzETjw. We also deployed an online demonstration system at https://drugwatch.net/.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 22 references that are in the map. First posted on arXiv 18 Jun 2024.
Builds on
5 of 22 references.
References · 5
- 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
- 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
- 2022Unified Structure Generation for Universal Information Extractioncited by 220
- 2022PHEE: A Dataset for Pharmacovigilance Event Extraction from Textcited by 36
- 2024Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Studycited by 11
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.