Building an Automatic Analysis System to Analyze Correlations between a Disease and Site-specific Cancers

• Main Authors: Jia-Li,Xu, 徐佳莉
• Other Authors: Jorng-Tzong Horng
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/cv32z5

碩士 === 國立中央大學 === 資訊工程學系 === 104 === Introduction: With the issue of cancer is being taken seriously, more and more cohort studies are conducted to investigate the risk of developing cancer. Therefore, the efficiency of research on the epidemiologic studies ought to be concerned. Currently, none of analysis systems have considered the correlations between a disease and all cancer types simultaneously. This study aims at implementing an automatic analysis system to analyze correlations between a disease and some of site-specific cancers in a large Taiwanese cohort. Methods: We build a website to instruct researchers to make a query step by step. After each step is performed, the query is check whether it’s complete by the system and sent to the system core to be transformed into corresponding SAS codes. Then, our system keeps executing the SAS file by the statistical software until the end of analysis. Finally, the system core converts the SAS output files into result tables and displays them on the website. Results: In order to verify our results by journals, we choose seven studies from different journals based on NHIRD or LHID. After that, we divided the results into three partitions to compare with them, including baseline of characteristics among patients with main disease, correlation between main disease and all cancers and correlation between main disease and specific cancer types. Although during verifying, there are some difference between the analytical results and the previous works, the similarities between them are in majority. Conclusions: In this thesis, an automated analysis system is implemented to analyze correlation between a disease and some of site-specific cancers. The results verified by the journals illustrate that our system is reliable and can provide similar results in comparison with journals in cancer-related cohort study.