https://www.selleckchem.com/products/thz1.html
One clinical feature, five CT features, and three radiomics features were selected, and three non-invasive models were built. Integration of the radiomics, CT, and clinical features model showed a better performance in predicting the risk of OVB, with an AUC of 0.89 (95% confidence interval [CI], 0.84-0.94) in the training dataset and 0.78 (95% CI, 0.68-0.87) in the validation dataset. The combination of radiomics, CT, and clinical features may have added value in the non-invasive prediction of OVB, enabling early prevention and treatment.
Like
Comment
Share
