Xiaobei Duan

Jiangmen, China

Last Updated: 09/26/2026

Save publications for later

Sign Up

Not sure about your diagnosis?

Check Your Symptoms

Found 16 publications

Factors associated with clinical outcomes of breast cancer based on glucose metabolic activity of subcutaneous adipose tissue.

Factors associated with clinical outcomes of breast cancer based on glucose metabolic activity of subcutaneous adipose tissue.

Journal: Frontiers in oncology

Published: October 10, 2025

Risk stratification for early-stage NSCLC progression: a federated learning framework with large-small model synergy.

Risk stratification for early-stage NSCLC progression: a federated learning framework with large-small model synergy.

Journal: Frontiers in oncology

Published: October 06, 2025

Prognostic value of integrating CT morphological features and PET volumetric metabolic parameters in surgically resected stage IA non-small cell lung cancer: a two-center retrospective study.

Prognostic value of integrating CT morphological features and PET volumetric metabolic parameters in surgically resected stage IA non-small cell lung cancer: a two-center retrospective study.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society

Published: July 16, 2025

Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model.

Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society

Published: May 20, 2025

Deep Learning-Based Multimodal Feature Interaction-Guided Fusion: Enhancing the Evaluation of EGFR in Advanced Lung Adenocarcinoma.

Deep Learning-Based Multimodal Feature Interaction-Guided Fusion: Enhancing the Evaluation of EGFR in Advanced Lung Adenocarcinoma.

Journal: Academic radiology

Published: January 09, 2025

Multimodal deep learning radiomics model for predicting postoperative progression in solid stage I non-small cell lung cancer.

Multimodal deep learning radiomics model for predicting postoperative progression in solid stage I non-small cell lung cancer.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society

Published: January 15, 2024

Computer-aided diagnosis of distal metastasis in non-small cell lung cancer by low-dose CT based radiomics and deep learning signatures.

Computer-aided diagnosis of distal metastasis in non-small cell lung cancer by low-dose CT based radiomics and deep learning signatures.

Journal: La Radiologia medica

Published: July 28, 2023

Identifying Solitary Granulomatous Nodules from Solid Lung Adenocarcinoma: Exploring Robust Image Features with Cross-Domain Transfer Learning.

Identifying Solitary Granulomatous Nodules from Solid Lung Adenocarcinoma: Exploring Robust Image Features with Cross-Domain Transfer Learning.

Journal: Cancers

Published: November 02, 2022

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.

Journal: European radiology

Published: August 03, 2022

A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinoma.

A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinoma.

Journal: European journal of radiology

Published: April 23, 2021

A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules.

A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society

Published: December 18, 2019

Whole-Lesion Computed Tomography-Based Entropy Parameters for the Differentiation of Minimally Invasive and Invasive Adenocarcinomas Appearing as Pulmonary Subsolid Nodules.

Whole-Lesion Computed Tomography-Based Entropy Parameters for the Differentiation of Minimally Invasive and Invasive Adenocarcinomas Appearing as Pulmonary Subsolid Nodules.

Journal: Journal of computer assisted tomography

Published: July 26, 2019

Showing 1-12 of 16

Last Updated: 09/26/2026