| Summary: | 碩士 === 淡江大學 === 資訊工程學系碩士在職專班 === 104 === Nowadays medical technology has improved rapidly; many patient of endometriosis can be treated with surgery, which enables the patient to be pregnable. Medical statistics data indicates many clinicians and researchers have confirmed that the therapy of ultrasound-guided aspiration with 95% ethanol for up to 7 minutes without extraction has the best result for ovarian endometrioma, however, only few of them have explored the relationship on the length of ethanol treatment time for patient with different conditions and the pain relief improvement rate of the patient. The effectiveness of the treatment is different in accordance to different patient condition; and the pain relief improvement rate is different in accordance to different treatments. This study implements data mining approach to explore the most effective treatment methods for patient pain relief. Due to the fact that there are too many data fields on patients, by applying the traditional statistical methods, like t-test or analysis of variance (ANOVA) methods would be difficult to find a suitable cut-off point to be divided into suitable groups for data analysis. Therefore, this study uses the decision tree algorithms to analyze the number of patient for pain-scale have improved or not in different treatment, and combined with statistical methods t-test, to compare the treatment of patients with pain improvement rate in order to understand what kind of treatment has better in pain-scale relief effect. Furthermore, compare the patient pain improvement condition on different treatments and understand what the most effective treatments in pain relief are. Ethanol for up to 7 minutes without extraction has the best result in pain relief except when the number of cyst exceed 4. In fact, after consulting with physicians the finding is that apart from lack of sample issue, endometriosis is difficult to be treated when large number of cyst is present, thus, regardless of which treatment is applied, the effectiveness is limited.
|
|---|
