AUTHOR=Yin Yajun , Lu Jiawei , Tong Jichun , Cheng Youshuang , Zhang Ke 

TITLE=Relationship between early lung adenocarcinoma and multiple driving genes based on artificial intelligence medical images of pulmonary nodules

JOURNAL=Frontiers in Genetics

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1142795

DOI=10.3389/fgene.2023.1142795

ISSN=1664-8021

ABSTRACT=Lung adenocarcinoma is one of the most common cancers in the world. Accurate diagnosis of pulmonary nodules is an important factor to reduce mortality. In the diagnosis of pulmonary nodules, artificial intelligence (AI) assisted diagnosis technology has been rapidly developed. Therefore, the test of its effectiveness is to promote its important role in clinical practice. This paper introduced the background of early lung adenocarcinoma and AI medical imaging of pulmonary nodules, and then conducted academic research on early lung adenocarcinoma and AI medical imaging, and finally summarized it with biological information. The analysis of the relationship between the four driving genes of group X and group Y in the experimental part showed that there were more gene abnormalities in invasive lung adenocarcinoma, and the maximum uptake value and uptake value function were also higher in metabolic value. However, there was no obvious correlation between the mutation of the four driving genes and the metabolic value, and the average accuracy of AI based medical images was 3.88% higher than that of traditional images. At the same time, with the development of high-throughput sequencing technology and bioinformatics, it has opened up a new way for the research of lung cancer tumor markers.