Colorectal Cancer Diagnosis with Complex Fuzzy Inference System

Abstract

Artificial intelligence has been applied in various fields including medicine. Cancer is one of the most common and dangerous diseases that need to be diagnosed for the best treatment. Herein, we introduce a new model using complex fuzzy inference system (CFIS) for colorectal cancer diagnosis. The time series characteristic of colorectal disease is signification in examination, diagnosis, and treatment. The model is implemented on a colonography dataset to evaluate the performance. The obtained results show that it gets high quality in comparison with some other compared methods.