| Summary: | 碩士 === 國立交通大學 === 生物資訊及系統生物研究所 === 106 === Nowadays, the colorectal cancer has become an increased incidence of cancer in Taiwan since the promotion in qualities of life and changes in eating habits. The risk factors for colorectal cancer include DNA repair genes, low fruit and vegetable consumption, high-meat diet, exercise, obesity, smoking, alcohol and so on will increase risk of getting colorectal cancer. Colorectal cancer often comes from growing polyps of which will become cancer over time. The cancer has spread through the lymph nodes and blood to other parts of the body. The standard of diagnosis of the colorectal cancer is the lymph node biopsy with H&E stain that is able to stage the colorectal cancer and to offer the diagnosis of the cancer and suggestions for the prognosis. In this study, the lymph node biopsies in colorectal cancer are provided by China Medical University. This study use techniques of image segmentation, feature extraction, feature selection and SVM to build a high accuracy prediction model to predict lymph node metastasis or not in colorectal cancer and analysis the degree of cancer of lymph nodes without observing tumor cells. This study used one colorectal cancer’s 4 lymph node biopsies as training data and 51 nuclei-based features to build a classification model to predict lymph node metastasis or not in colorectal cancer. The result shows that the AUC from 10-fold validation of training data is 0.9972. The AUC of the prediction for the same patient is 0.9008 and the accuracy of the prediction for the patient with colorectal cancer is 96.55%. In short, the discrimination capacity of the classification model is good. Moreover, this study used this model to predict 8 whole lymph node biopsies to get the decision values and used heat map to show the degree of cancer.
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