Research on Medical Information Extraction and Recognition of Lung Tumor Based on Convolutional Neural Network

With the improvement of the social economy, lung cancer has gradually become one of the main reasons for endangering human security. The tumor is benign or malignant, which can reduce the cumbersome examination in the early stage, prevent unnecessary surgery, reduce the psychological and physical pain of patients, and improve the survival rate of patients. As a common method of treatment and detection of treatment response in the medical field, the medical image has become the main technical means of cancer diagnosis and treatment in the clinic. This paper studies the extraction and recognition technology of lung tumor medical information based on a convolutional neural network (CNN), and the method used is CNN. CNN provides an end-to-end learning model. The parameters in the model can be trained by the traditional gradient descent method. The trained CNN can learn the features in the image, and complete the extraction and classification of image features. After research, the algorithm in this paper is effective and suitable for wide use.