Applying Time Interval Sequential Pattern Mining Approach to Investigate the Patients' Medication Sequence and Length of Stays Before Suffering Steven Johnson Syndrome
| Autor: | Chih-Chien Chang, 張之倩 |
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| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 105 With plenty of convenient medical resources, it is easy for patients to see a doctor in several hospitals with the same disease or let patients get duplicated medication or interactions between multiple drugs. On the other hand, in the investigation of Taiwan Drug relief system, it indicated that Stevens Johnson Syndrome (shortly as SJS in the following paper) was the main case for application. Therefore, the aim of this study is to use the time interval sequential pattern to explore the patients’ medication sequence and length of stays before suffering Steven Johnson Syndrome. However, the conventional sequential pattern mining methods only provide the chronological order but it will ignore the time-interval between the items. For this reason, using the approach to mine the patients who got SJS, it might lead to neglecting the interactions between the medicines which would cause an increase in morbidity of SJS. Consequently, the research of this study will consider the influences of time interval in the above methods to discuss the time-interval sequential pattern of patients who suffered from SJS. This research has retrieved patients’ medical records from Taiwan National Health Insurance Research Database and connected the relative data for preprocessing. To easily analyze the data, pharmacological classification, admission and discharge were classified and coded. In addition, K-means approach was initially adopted to analyze the time interval between taking medicines and length of stays to categorize in consecutive days. After that, we can apply high frequency pattern from the database to discover correlation between receiving medicines and length of stays with time interval sequential pattern. The results of the research can be regards as a reference for medical decision making and a benefit to the potential patients. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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