| dc.contributor.advisor | Ly, Le Thi | |
| dc.contributor.author | Khanh, Le Phuoc Bao | |
| dc.date.accessioned | 2018-08-28T02:43:00Z | |
| dc.date.available | 2018-08-28T02:43:00Z | |
| dc.date.issued | 2017 | |
| dc.identifier.other | 022003720 | |
| dc.identifier.uri | http://keep.hcmiu.edu.vn:8080/handle/123456789/2726 | |
| dc.description.abstract | Electronic medical records (EMR) is not only a great resource for patient information management but also for important and long term medical research. On this research EMR database of diabetes patients is used to find the unknown-side effect of patients. Text mining is performed with the library that is side effects database from SIDER and then compare with the drug-side effects data to find hidden side effects. If there is no relationship to diabetes found, these hidden side effects can be considered as hypothesis unknown side effects. In total there are 2 unknown side effects are Fall and Sedation that are caused by the method of treatment or by drug combination or by drug itself. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | International University - HCMC | en_US |
| dc.subject | Adverse drug reation; Electronic medical records; Diabetes type 2 | en_US |
| dc.title | Investigation of adverse drug reation (ADR) from electronic medical records (EMR) for type 2 diabetes patients | en_US |
| dc.type | Thesis | en_US |
