In order to assist doctors in planning treatment and review programs for non-small cell lung cancer (NSCLC) patients

a prognostic survival analysis method based on CT radiomics was proposed. First

we segmented the tumor areas in the lung CT images. Then

we extracted and optimized the radiomics features. Finally

the optimized features and the patients’ prognosis survival were taken as input

and the prognostic analysis model was constructed by using machine learning method to predict the prognosis survival time range of the patients. The data of 124 NSCLC patients were selected and the clinical significance of 3-year survival was used as the predictive limit to predict the prognosis survival time range. The experimental results showed the prediction accuracy of the model reached 91.9%

which could effectively assist doctors to carry out more accurate assessment and develop more personalized treatment and review programs for NSCLC patients.