Utilizing the sine function in radiation treatment of bladder cancer prediction

• Main Authors: LIN,TSAI-YU, 林才煜
• Other Authors: 蔡東亦
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/21601374720684236573

碩士 === 樹德科技大學 === 資訊管理系碩士班 === 99 === Radiotherapy may preserve normal bladder function, and therefore plays an increasingly important role in treatment for selected patients with bladder cancer. It is known that some biological protein factors influence radiation response to bladder cancer. Nevertheless, one or two specific proteins may not be sufficient to predict the effect of radiotherapy, and analyzing multiple oncoproteins and tumor suppressor proteins may achieve better predictions. However, researchers do not yet have an effective technique to evaluate the outcome of radiotherapy on multiple proteins using a very limited number of samples from patients. A modified Mega-Trend-Diffusion technique is proposed to solve the small dataset problem. This research used the neural network to obtain data, the data showing a residual rate of bladder cancer. The proposed prediction model can help patients to decide if it is appropriate to do radiation therapy in bladder cancer.