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Deep Learning Nomogram for Gastric Cancer NACT Response by Jason Huang is a document available to read on EtoBox.

What is Deep Learning Nomogram for Gastric Cancer NACT Response about?

This study developed and validated a deep learning radiomics nomogram (DLRN) to predict the response to neoadjuvant chemotherapy (NACT) in patients with locally advanced gastric cancer (LAGC) using CT images and clinical features. The DLRN demonstrated strong predictive performance with AUCs ranging from 0.804 to 0.829 across multiple validation cohorts, outperforming traditional clinical models. The findings suggest that DLRN can aid in personalized treatment strategies for LAGC patients by accurately pred

Author

Jason Huang

Language

EN