EP1.17-02 Artificial Intelligence in the Qualitative Study of Pulmonary Nodules by Analyzing the Genetic Map and Imaging Data of Lung Adenocarcinoma

Abstract

Artificial intelligence is the most influential technology for the future and the hottest research and technology at present. Lung cancer is the most common malignant tumor with the highest morbidity and mortality. By analyzing the genetic characteristics and imaging of patients with lung adenocarcinoma, this study aims to analyze the pulmonary nodules in the susceptible population to find the most characteristic. Gansu province is an economically backward province in northwest China, with a poor environment, poor living conditions, low level of medical and health services, mainly rural population, per capita income less than 5,000 yuan, and a high incidence and mortality of lung cancer and esophageal cancer. Most patients come to the hospital for treatment are in the middle and late stage of lung cancer, and often miss the best time for treatment. Even if they come to the hospital for treatment, there is no good effect, and bring huge economic burden and family burden. The early diagnosis and treatment of lung cancer is particularly important. Artificial intelligence for lung cancer and population census is an economical, convenient and accurate technology, which will bring huge benefits to people”s health. In this study, the imaging data of diagnosed lung adenocarcinoma patients with pulmonary nodules and the gene sequencing and mutation point of pathological specimens were studied by artificial intelligence, and the lung cancer genes identified by NICC were compared with deep learning to produce relatively complete learning software. The software was used to select the selected sample population of people with high risk of lung cancer regions, and then the postoperative pathology of pulmonary nodules highly suspected of lung cancer was input into the database, and the preoperative diagnosis of AI was compared and studied to optimize the software. It is hoped that this study can develop a set of artificial intelligence software with high accuracy and sensitivity, and then carry out early diagnosis and treatment of lung cancer in high-risk groups. Provide research basis for the genetics of lung adenocarcinoma and the early invasion characteristics of lung adenocarcinoma. This study could develop a set of artificial intelligence software with high accuracy and sensitivity, and then carry out early diagnosis and treatment of lung cancer in high-risk groups. Provide research basis for the genetics of lung adenocarcinoma and the early invasion characteristics of lung adenocarcinoma.