| アブストラクト | BACKGROUND: Exploration of the Adverse Event Reporting System (AERS) data by a wide scientific community is limited due to several factors. First, AERS data must be intensively preprocessed to be converted into analyzable format. Second, application of the currently accepted disproportional reporting measures results in false positive signals. METHODS: We proposed a data mining strategy to improve hypothesis generation with respect to potential associations. RESULTS: By numerous examples, we illustrate that our strategy controls the false positive signals. We implemented a free online tool, AERS spider (www.chemoprofiling.org/AERS). CONCLUSIONS: We believe that AERS spider would be a valuable tool for drug safety experts. |
|---|
| ジャーナル名 | Pharmacoepidemiology and drug safety |
|---|
| Pubmed追加日 | 2014/3/29 |
|---|
| 投稿者 | Grigoriev, Igor; zu Castell, Wolfgang; Tsvetkov, Philipp; Antonov, Alexey V |
|---|
| 組織名 | Helmholtz Zentrum Munchen GmbH, Department of Scientific Computing, Neuherberg,;Germany. |
|---|
| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/24677538/ |
|---|
