Xiaoyan Huang

Volumetric modulated arc therapy (VMAT) planning is complex and time-consuming. This study proposes a direct VMAT plan generation method for cervical cancer, enhanced by a physics-guided 3D dose-domain supervision strategy to ensure dosimetric quality.

To develop a multi-omics data integration method based on ensemble learning to construct a prognostic decision model for MRI-guided radiotherapy in gliomas, providing reliable reference for clinical decision-making.