This system applies artificial intelligence (AI) to the recognition and auxiliary diagnosis of lung CT images. It establishes a high-quality training set based on large image data, expert annotations, and pathological data. Through convolutional neural networks and other deep learning algorithms, it simulates training and optimization to develop an AI system that can automatically and quickly identify lung nodules on CT images, especially small lung nodules, and automatically assess the benign or malignant nature of the nodules. This aims to establish an efficient and accurate CT-assisted diagnostic method, improving clinical reading efficiency and accuracy. Currently, we have one software copyright for early screening of lung cancer, and we are also applying for an invention patent. We have developed the initial version of a lung nodule imaging recognition system, which includes functions such as nodule identification and localization, benign/malignant determination, and tissue typing. This AI technology participated in the recent global 'Tianchi' AI Lung Nodule Diagnosis Competition organized by Alibaba and stood out among many participating institutions worldwide. The first season advanced to the playoffs with a global ranking of eighth.