Area of research
Radiology, Nuclear Medicine and Imaging · Pulmonary and Respiratory Medicine
Research interest
Research focused on Nomogram and Radiology, with related work in Radiomics, Malignancy, Lung. Notable publications include 'Deep Learning Radiomics Features of Mediastinal Fat and Pulmonary Nodules on Lung CT Images Distinguish Benignancy and Malignancy', 'Deep learning-based CT image for pulmonary nodule classification with intrathoracic fat: A multicenter study', and 'Multi-region nomogram for predicting central lymph node metastasis in papillary thyroid carcinoma using multimodal imaging: A multicenter study'.
Multi-region nomogram for predicting central lymph node metastasis in papillary thyroid carcinoma using multimodal imaging: A multicenter study
Multimodal deep learning: tumor and visceral fat impact on colorectal cancer occult peritoneal metastasis
Deep Learning Radiomics Features of Mediastinal Fat and Pulmonary Nodules on Lung CT Images Distinguish Benignancy and Malignancy
Deep learning-based CT image for pulmonary nodule classification with intrathoracic fat: A multicenter study
Dual biomarkers CT-based deep learning model incorporating intrathoracic fat for discriminating benign and malignant pulmonary nodules in multi-center cohorts
An Integrated Nomogram Combining Deep Learning and Radiomics for Predicting Malignancy of Pulmonary Nodules Using <scp>CT</scp> ‐Derived Nodules and Adipose Tissue: A Multicenter Study
Incorporating adipose tissue into a CT-based deep learning nomogram to differentiate granulomas from lung adenocarcinomas