DrugWatch: A Comprehensive Multi-Source Data Visualisation Platform for Drug Safety Information
June 18, 2024 Β· Declared Dead Β· π Annual Meeting of the Association for Computational Linguistics
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Authors
Artem Bobrov, Domantas Saltenis, Zhaoyue Sun, Gabriele Pergola, Yulan He
arXiv ID
2407.01585
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
cs.IR
Citations
1
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
4 months ago
Abstract
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/.
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