Please use this identifier to cite or link to this item:
https://doi.org/10.1186/s13326-020-00221-1
Title: | Neural side effect discovery from user credibility and experience-assessed online health discussions | Authors: | Van-Hoang Nguyen Kazunari Sugiyama Min-Yen Kan Kishaloy Halder |
Keywords: | Online health communities Drug side effect discovery Credibility analysis Deep learning Natural language processing |
Issue Date: | 8-Jul-2020 | Publisher: | Journal of Biomedical Semantics | Citation: | Van-Hoang Nguyen, Kazunari Sugiyama, Min-Yen Kan, Kishaloy Halder (2020-07-08). Neural side effect discovery from user credibility and experience-assessed online health discussions. Journal of Biomedical Semantics 11 (5). ScholarBank@NUS Repository. https://doi.org/10.1186/s13326-020-00221-1 | Rights: | Attribution 4.0 International | Abstract: | Health 2.0 allows patients and caregivers to conveniently seek medical information and advice via e-portals and online discussion forums, especially regarding potential drug side effects. Although online health communities are helpful platforms for obtaining non-professional opinions, they pose risks in communicating unreliable and insufficient information in terms of quality and quantity. Existing methods in extracting user-reported adverse drug reactions (ADRs) in online health forums are not only insufficiently accurate as they disregard user credibility and drug experience, but are also expensive as they rely on supervised ground truth annotation of individual statement. We propose a NEural ArchiTecture for Drug side effect prediction (NEAT), which is optimized on the task of drug side effect discovery based on a complete discussion while being attentive to user credibility and experience, thus, addressing the mentioned shortcomings. We train our neural model in a self-supervised fashion using ground truth drug side effects from mayoclinic.org. NEAT learns to assign each user a score that is descriptive of their credibility and highlights the critical textual segments of their post. | Source Title: | Journal of Biomedical Semantics | URI: | https://scholarbank.nus.edu.sg/handle/10635/172412 | DOI: | 10.1186/s13326-020-00221-1 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements Students Publications |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
s13326-020-00221-1.pdf | 1.61 MB | Adobe PDF | OPEN | None | View/Download |
This item is licensed under a Creative Commons License