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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mingzhen Zhao Bo Xu Hongfei Lin Zhihao Yang Jian Wang |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Comput. Sci. & Technol., Dalian Univ. of Technol., Dalian, China (Mingzhen Zhao; Bo Xu; Hongfei Lin; Zhihao Yang; Jian Wang) |
| Abstract | In these years, the adverse drug reactions (ADRs) have seriously impacted the people's health, and adverse drug event reporting systems become a key means to monitor the drug safety, in which healthcare professionals or drug consumers can submit the adverse drug event reports based on their experience or professional knowledge. However, with the increase of drugs, the number of the submitted reports increases rapidly, making it more and more difficult to capture all the ADRs manually. To tackle the problem, we develop a novel system to compute the similarities among the drugs and adverse reactions automatically from the reports. In the method, we represent the mentions of drugs and adverse reactions as distributed vectors using the skip-gram model, and discover the most potential adverse drug reactions based on the similarities. |
| Sponsorship | IEEE |
| Starting Page | 1765 |
| Ending Page | 1767 |
| File Size | 320394 |
| Page Count | 3 |
| File Format | |
| e-ISBN | 9781467367998 |
| DOI | 10.1109/BIBM.2015.7359955 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-11-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Drugs adverse drug reactions skip-gram model Manuals distributed vectors Cancer |
| Content Type | Text |
| Resource Type | Article |
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