Recognition of Lung Adenocarcinoma-specific Gene Pair Based on Genetic Algorithm and Establishment of a Deep Learning Prediction Model

AIM AND OBJECTIVE: Lung cancer is a disease with a dismal prognosis and is the major cause of cancer deaths in many countries. Nonetheless, rapid technological developments in genome science guarantees more effective prevention and treatment strategies. MATERIALS AND METHODS: In this study, genes were pair-matched and screened for lung adenocarcinomaspecific gene relationships. False positives due to fluctuations in single gene expression were avoided and the stability and accuracy of the results was improved. RESULTS: Finally, a deep learning model was constructed with machine learning algorithm to realize the clinical diagnosis of lung adenocarcinoma in patients. CONCLUSION: Comparing with the traditional methods which takes ingle gene as a feature, the relative difference between gene pairs is a higher order feature, leverage high-order features to build the model can avoid instability caused by a single gene mutation, making the prediction results more reliable.