Area of research
Otorhinolaryngology · Surgery
Research interest
Research interests include Head and Neck Cancer Studies, Head and Neck Surgical Oncology, Radiomics and Machine Learning in Medical Imaging, and Esophageal Cancer Research and Treatment.
Toripalimab Combination Therapy Without Concurrent Cisplatin for Nasopharyngeal Carcinoma
Ninth Version of the AJCC and UICC Nasopharyngeal Cancer TNM Staging Classification
TiCNet: Transformer in Convolutional Neural Network for Pulmonary Nodule Detection on CT Images
Hyperfractionation compared with standard fractionation in intensity-modulated radiotherapy for patients with locally advanced recurrent nasopharyngeal carcinoma: a multicentre, randomised, open-label, phase 3 trial
Evolutionary route of nasopharyngeal carcinoma metastasis and its clinical significance
Medial retropharyngeal nodal region sparing radiotherapy versus standard radiotherapy in patients with nasopharyngeal carcinoma: open label, non-inferiority, multicentre, randomised, phase 3 trial
Semi‐automatic fine delineation scheme for pancreatic cancer
Deep learning–based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study
Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma
Unambiguous advanced radiologic extranodal extension determined by MRI predicts worse outcomes in nasopharyngeal carcinoma: Potential improvement for future editions of N category systems
3-D RoI-Aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation
Channel-Attention U-Net: Channel Attention Mechanism for Semantic Segmentation of Esophagus and Esophageal Cancer
Graph‐convolutional‐network‐based interactive prostate segmentation in MR images
Influence of tumor necrosis on treatment sensitivity and long-term survival in nasopharyngeal carcinoma
Prognostic significance of quantitative metastatic lymph node burden on magnetic resonance imaging in nasopharyngeal carcinoma: A retrospective study of 1224 patients from two centers
Differentiation Between Benign and Nonbenign Meningiomas by Using Texture Analysis From Multiparametric MRI
Proposed modifications and incorporation of plasma Epstein‐Barr virus DNA improve the TNM staging system for Epstein‐Barr virus‐related nasopharyngeal carcinoma
PSNet: prostate segmentation on MRI based on a convolutional neural network
The value of detailed MR imaging report of primary tumor and lymph nodes on prognostic nomograms for nasopharyngeal carcinoma after intensity-modulated radiotherapy
Deep convolutional neural network for prostate MR segmentation
Prognostic Impact of Plasma Epstein-Barr Virus DNA in Patients with Nasopharyngeal Carcinoma Treated using Intensity-Modulated Radiation Therapy
Computer-aided Detection of Prostate Cancer with MRI
A supervoxel‐based segmentation method for prostate MR images
Development and validation of quality of life scale of nasopharyngeal carcinoma patients: the QOL-NPC (version 2)
Superpixel-Based Segmentation for 3D Prostate MR Images
Prospective Study of Tailoring Whole-Body Dual-Modality [<sup>18</sup>F]Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography With Plasma Epstein-Barr Virus DNA for Detecting Distant Metastasis in Endemic Nasopharyngeal Carcinoma at Initial Staging
A four‐miRNA signature identified from genome‐wide serum miRNA profiling predicts survival in patients with nasopharyngeal carcinoma
Serologic biomarkers of Epstein–Barr virus correlate with TNM classification according to the seventh edition of the UICC/AJCC staging system for nasopharyngeal carcinoma
Is primary tumor volume still a prognostic factor in intensity modulated radiation therapy for nasopharyngeal carcinoma?