Area of research
Radiology, Nuclear Medicine and Imaging · Pulmonary and Respiratory Medicine
Research interest
Research focused on Immunotherapy and Radiomics, with related work in Cohort, Nomogram, Retrospective cohort study. Notable publications include 'Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study', 'Radiomic signature of 18 F fluorodeoxyglucose PET/CT for prediction of gastric cancer survival and chemotherapeutic benefits', and 'Noninvasive Prediction of Occult Peritoneal Metastasis in Gastric Cancer Using Deep Learning'.
Noninvasive Imaging Assessment of Tertiary Lymphoid Structures and Immunotherapy Response in Gastric Cancer: A Multicenter Study
Multimodal radiopathomics signature for prediction of response to immunotherapy-based combination therapy in gastric cancer using interpretable machine learning
TME-guided deep learning predicts chemotherapy and immunotherapy response in gastric cancer with attention-enhanced residual Swin Transformer
Comprehensive assessment of immune context and immunotherapy response via noninvasive imaging in gastric cancer
Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics
Biology-guided deep learning predicts prognosis and cancer immunotherapy response
Non-invasive CT imaging biomarker to predict immunotherapy response in gastric cancer: a multicenter study
Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning
Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study
Noninvasive imaging of the tumor immune microenvironment correlates with response to immunotherapy in gastric cancer
1284 Biology-guided deep learning predicts prognosis and cancer immunotherapy response
Noninvasive Prediction of Occult Peritoneal Metastasis in Gastric Cancer Using Deep Learning
Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study
Subregional Radiomics Analysis of PET/CT Imaging with Intratumor Partitioning: Application to Prognosis for Nasopharyngeal Carcinoma
Radiomic signature of<sup> 18</sup>F fluorodeoxyglucose PET/CT for prediction of gastric cancer survival and chemotherapeutic benefits