| dc.contributor | 資訊管理學系 | zh_Tw |
| dc.creator (作者) | Tseng, SuFeng;Frank, H. | en_US |
| dc.creator (作者) | 鄭夙芬 | zh_TW |
| dc.date (日期) | 2017-03 | en_US |
| dc.date.accessioned | 3-Aug-2017 14:16:21 (UTC+8) | - |
| dc.date.available | 3-Aug-2017 14:16:21 (UTC+8) | - |
| dc.date.issued (上傳時間) | 3-Aug-2017 14:16:21 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/111631 | - |
| dc.description.abstract (摘要) | Over a 3-year period, fever is always the most frequent icd9 code in inpatient health records including admission and discharge notes, and over 25% accounted for the top 6 frequent ICD9 codes. In this study, we illustrated the fever-related diseases and comorbidity. Given that 81.193% of fever-related ICD9 codes appear within 14 times, the association rules performed for fever-related comorbidity still managed to improve care with 48.077% coverage rate by proper CPOE. © 2016 IEEE. | en_US |
| dc.format.extent | 206 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016, , 128-132 | en_US |
| dc.relation (關聯) | 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016; Las Vegas; United States; 15 December 2016 到 17 December 2016; 類別編號E6020; 代碼 126900 | en_US |
| dc.subject (關鍵詞) | Artificial intelligence; Codes (symbols); Epidemiology; Co morbidities; Coverage rate; fever; Health records; ICD9-CM; inpatient admission; Hospitals | en_US |
| dc.title (題名) | Characteristics of inpatient fever: A case in teaching hospital | en_US |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1109/CSCI.2016.0031 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1109/CSCI.2016.0031 | |
