EARLY STAGE LUNG CANCER DIAGNOSIS BASED ON NEURAL NETWORK ENSEMBLE

In this paper, pathological diagnosis is combined with computer techniques for early stage diagnosis of lung cancer. Firstly, punctured samples of lung cancer are processed by digital image technique, extracting morphologic and chromatic features. Then, the cell images are analyzed by neural network ensemble with a two-layered architecture and a specific voting scheme. Experiments and the probation of a prototype system show that both the overall misdiagnosis rate and the rate of missed diagnosis of lung cancer sufferers are lower than that of the single neural network and commonly-used neural network ensemble methods.