Rule Generation for Gallbladder Cancer Prediction Using Decision Tree Classifier

Cancer is a disease, where cells grow out of control, divide and attack other tissues of the patient. There are many forms of cancer, among which the ?Gallbladder Cancer? is relatively uncommon. This cancer can be permanently cured only by removing the Gallbladder. Else, the patient must be treated with high dosage of medicine for the survival, which in turn cures the disease but reduces the lifetime of the patient. Instead, if the gall bladder cancer is predicted at the earlier stage, it can be cured by treating with less dosage of medicines. In the proposed methodology, earlier detection of gall bladder cancer is done through imaging, which contains three major steps as, Pre-processing, Feature Extraction and Feature Classification. The noise in the image can be removed using Pre-processing step. The essential features for the cancer prediction can be extracted from the segmented image. Further, using decision tree algorithm, gallbladder cancer prediction is done.