Name
Title | ||
|---|---|---|
Identifying Adverse Drug Events From Social Media Using An Improved Semisupervised Method. |
Abstract | ||
|---|---|---|
Adverse drug event (ADE) is a serious health concern. Social media has provided patients a broad platform to share their ADE experiences, impelling the development of social media-based pharmacovigilance. However, social media analysis of ADEs presents several important challenges that need to be addressed for high-performing ADE identification. To address these challenges, a feature weighted-base... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MIS.2019.2893158 | IEEE Intelligent Systems |
Keywords | Field | DocType |
Drugs,Feature extraction,Social network services,Classification algorithms,Semantics,Intelligent systems,Semisupervised learning | Data science,Social media,Intelligent decision support system,Computer science,Knowledge management,Feature extraction,Pharmacovigilance,Statistical classification,Semantics | Journal |
Volume | Issue | ISSN |
34 | 2 | 1541-1672 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||