ResearcherChongqing UniversityActive in the last 2 years
Zhuoyue Tang
Matched on ORCID iD 0000-0002-1433-5966; OpenAlex author ID A5050660113. Sources: OpenAlex.
Their work
- Papers
- 7 (first author 0, last author 7)
- Trials
- 0
- Grants
- 0
- Labs led
- 1
- Collaborators
- 7
2022: 1 paper · 2023: none · 2024: 4 papers · 2025: 1 paper · 2026: 1 paper
Papers 7
- Radiomics analysis of dual-energy CT-derived iodine maps for predicting histopathologic grading of pancreatic ductal adenocarcinoma: a two-center study. Last author DOI 10.3389/fmed.2026.1769626↗
- Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal adenocarcinoma. Last author DOI 10.1186/s12880-025-01664-7↗
- Development of a CT radiomics nomogram for preoperative prediction of Ki-67 index in pancreatic ductal adenocarcinoma: a two-center retrospective study. Last author DOI 10.1007/s00330-023-10393-w↗
- Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy com… Last author DOI 10.1186/s13244-024-01617-8↗
- Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-based quantitative parameters to predict hi… Last author DOI 10.1186/s13244-024-01864-9↗
- A nomogram based on dual-layer detector spectral computed tomography quantitative parameters and morphological quantitative indicator for distinguishing metast… Last author DOI 10.21037/qims-23-1624↗
- Feasibility of a CT-based lymph node radiomics nomogram in detecting lymph node metastasis in PDAC patients. Last author DOI 10.3389/fonc.2022.992906↗
Closest collaborators
The 7 strongest of 7 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Zuhua Song · 5 shared papers, 2024–2026 · strength 1.23
- Paper Radiomics analysis of dual-energy CT-derived iodine maps for predicting histopathologic grading of pancreatic ductal ad… DOI 10.3389/fmed.2026.1769626↗
- Paper Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal … DOI 10.1186/s12880-025-01664-7↗
- Paper Development of a CT radiomics nomogram for preoperative prediction of Ki-67 index in pancreatic ductal adenocarcinoma: … DOI 10.1007/s00330-023-10393-w↗
- Dan Zeng · 5 shared papers, 2024–2026 · strength 1.22
- Paper Radiomics analysis of dual-energy CT-derived iodine maps for predicting histopathologic grading of pancreatic ductal ad… DOI 10.3389/fmed.2026.1769626↗
- Paper Radiomics analysis of dual-layer detector spectral CT-derived iodine maps for predicting Ki-67 PI in pancreatic ductal … DOI 10.1186/s12880-025-01664-7↗
- Paper Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-bas… DOI 10.1186/s13244-024-01864-9↗
- Youjia Wen · 4 shared papers, 2022–2024 · strength 0.73
- Paper Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-bas… DOI 10.1186/s13244-024-01864-9↗
- Paper A nomogram based on dual-layer detector spectral computed tomography quantitative parameters and morphological quantita… DOI 10.21037/qims-23-1624↗
- Paper Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with r… DOI 10.1186/s13244-024-01617-8↗
- Qian Liu · 2 shared papers, 2022–2024 · strength 0.34
- Paper Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with r… DOI 10.1186/s13244-024-01617-8↗
- Paper Feasibility of a CT-based lymph node radiomics nomogram in detecting lymph node metastasis in PDAC patients. DOI 10.3389/fonc.2022.992906↗
- Xinwei Wang · 1 shared paper, 2026 · strength 0.33
- Qian Li · 1 shared paper, 2024 · strength 0.20
- Qian Li · 1 shared paper, 2022 · strength 0.15
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.