Diagnosis Expert System for Oesophagus Cancer in Early Stage

Esophageal cancer is one of the most common malignant tumors in Henan Province and videoendoscope is an invaluable tool for the diagnosis of early esophageal cancer. Therefore, we propose a diagnosis expert system for the diagnosis of early esophageal cancer on the basis of videoendoscope. We apply the Bag-of-Words model to get the feature representations and group the features using the Information Bottleneck method. Then we build the rule database by the aid of expert-doctors. Finally, we use the Petri net as the inference engine. Real Application shows that the accuracy of the proposed expert system is over 95%.