Article Versions Notes

Zhu K, Tong J, Duan Y, Li Y, Feng Y, Han Y, Xiao X, Han Z, Xia S. Deep Learning-Derived Pathomic Features Predict NCIT Efficacy in Resectable Locally Advanced ESCC: Clinical Utility and Mechanistic Insights. Current Oncology. 2026; 33(3):136. https://doi.org/10.3390/curroncol33030136

Zhu, Kunrui, Jie Tong, Yaqi Duan, Yiming Li, Yanqi Feng, Yuelin Han, Xiangtian Xiao, Zhuoyan Han, and Shu Xia. 2026. "Deep Learning-Derived Pathomic Features Predict NCIT Efficacy in Resectable Locally Advanced ESCC: Clinical Utility and Mechanistic Insights" Current Oncology 33, no. 3: 136. https://doi.org/10.3390/curroncol33030136

Zhu, K., Tong, J., Duan, Y., Li, Y., Feng, Y., Han, Y., Xiao, X., Han, Z., & Xia, S. (2026). Deep Learning-Derived Pathomic Features Predict NCIT Efficacy in Resectable Locally Advanced ESCC: Clinical Utility and Mechanistic Insights. Current Oncology, 33(3), 136. https://doi.org/10.3390/curroncol33030136