| Summary: | 碩士 === 國立虎尾科技大學 === 工業工程與管理研究所 === 99 === The bladder cancer is the secondly common prevalent urinary tract cancer, leading to a death rate of 2.4% in average. Especially in the area of high Blackfoot prevalence, there also demonstrates a tendency of higher lung cancer and bladder cancer occurrence rates arising from residents’ drinking well water. When in classified by histopathology, the bladder cancer can be separate into from Phase 0 to Phase 4. In the preliminary Phase 0 and Phase 1, the effective medical treatment can be achieved by uncomplicated Transurethral Resection of Bladder Tumor (TUR-BT). For the Phase 2 and Phase 3, the mostly adopted medical treatment method is the Radical Cystectomy. Both the Radical Cystectomy and the TUR-BT are already adopted into the insurance coverage of fulfillment items of DRG (Diagnosis Related Groups) of the national healthcare insurance. For intending to explore those aforesaid two surgeries under such prerequisites, it has been submitted an application by the research to the Bureau of National Healthcare Insurance for getting access to database of between years 2006 and 2009 to be adopted as the research objects in conjunction the evaluation items including: conducting comparisons on between the average medical treatment costs for excessive length of stay for the Radical Cystectomy, and that for the average length of stay for TUR-BT.
After the empirical study analysis is conducted, it has been established 17 prediction models belonging to Artificial Intelligence Model for estimating the length of stay, and 9 models for predicting the excessive length of stay for Radical Cystectomy; meanwhile, another 8 models for predicting the average length of stay for the TUR-BT. In regard of the prediction models for excessive length of stay for the Radical Cystectomy, the One-side SVM prediction model demonstrates better analysis results than other models with an average precision rate of up to 80.7% and a value of 0.71 in the average distribution area under the ROC Curve graph. Meanwhile, after the BPN is conducted, the searched best precision is applied in the CBT for prediction the length of stay of the TUR-BT can deliver a better prediction and precision function. Its precision rate is 85.23% and the value of the distribution area under the ROC curve graph is up to 0.78. In case of conducing comparisons on medical costs, this research has created a CBR-orientation medical cost prediction system for each of the two surgeries respectively. Each of their similarity levels is 95.405、98.85. In term of conducting standard deviation analysis for medical costs, both two can be judged by the professional physicians by perpetually increment or revision on different cases for enhancement of the system database for enabling such the system’s prediction concerning medical costs more compliable with the actual situations.
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