ResearcherShanghai Jiao Tong UniversityActive in the last 2 years
Xiaohua Qian
Matched on ORCID iD 0000-0002-6548-6801; OpenAlex author ID A5063759279, A5137420938. Sources: OpenAlex.
Their work
- Papers
- 13 (first author 0, last author 10)
- Trials
- 0
- Grants
- 0
- Labs led
- 1
- Collaborators
- 19
2021: 2 papers · 2022: 3 papers · 2023: 5 papers · 2024: 1 paper · 2025: 1 paper · 2026: 1 paper
Papers 13
- A clinician-centric intelligent method towards reliable pancreatic cancer vascular invasion assessment: a retrospective, multi-centre study. Last author DOI 10.1016/j.lanwpc.2026.101890↗
- A Dual-Task Synergy-Driven Generalization Framework for Pancreatic Cancer Segmentation in CT Scans. Last author DOI 10.1109/tmi.2025.3566376↗
- A causality-inspired generalized model for automated pancreatic cancer diagnosis. Last author DOI 10.1016/j.media.2024.103154↗
- A dual-transformation with contrastive learning framework for lymph node metastasis prediction in pancreatic cancer. Last author DOI 10.1016/j.media.2023.102753↗
- Generalized pancreatic cancer diagnosis via multiple instance learning and anatomically-guided shape normalization. Last author DOI 10.1016/j.media.2023.102774↗
- A deep-learning radiomics-based lymph node metastasis predictive model for pancreatic cancer: a diagnostic study. Co-author DOI 10.1097/js9.0000000000000469↗
- Causality-Driven Graph Neural Network for Early Diagnosis of Pancreatic Cancer in Non-Contrast Computerized Tomography. Last author DOI 10.1109/tmi.2023.3236162↗
- Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma. Co-author DOI 10.3389/fonc.2023.1074445↗
- A dual meta-learning framework based on idle data for enhancing segmentation of pancreatic cancer. Last author DOI 10.1016/j.media.2021.102342↗
- Utilizing GCN and Meta-Learning Strategy in Unsupervised Domain Adaptation for Pancreatic Cancer Segmentation. Last author DOI 10.1109/jbhi.2021.3085092↗
- Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation. Last author DOI 10.1109/tmi.2021.3104460↗
- Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutation in Pancreatic Cancer. Last author DOI 10.1109/tmi.2020.3035789↗
- Differentiating TP53 Mutation Status in Pancreatic Ductal Adenocarcinoma Using Multiparametric MRI-Derived Radiomics. Co-author DOI 10.3389/fonc.2021.632130↗
Closest collaborators
The 19 strongest of 19 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Jun Li · 4 shared papers, 2022–2025 · strength 0.92
- Paper A Dual-Task Synergy-Driven Generalization Framework for Pancreatic Cancer Segmentation in CT Scans. DOI 10.1109/tmi.2025.3566376↗
- Paper Utilizing GCN and Meta-Learning Strategy in Unsupervised Domain Adaptation for Pancreatic Cancer Segmentation. DOI 10.1109/jbhi.2021.3085092↗
- Paper A dual meta-learning framework based on idle data for enhancing segmentation of pancreatic cancer. DOI 10.1016/j.media.2021.102342↗
- Xiahan Chen · 4 shared papers, 2021–2023 · strength 0.78
- Paper A dual-transformation with contrastive learning framework for lymph node metastasis prediction in pancreatic cancer. DOI 10.1016/j.media.2023.102753↗
- Paper Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutat… DOI 10.1109/tmi.2020.3035789↗
- Paper Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation. DOI 10.1109/tmi.2021.3104460↗
- Xiaozhu Lin · 4 shared papers, 2021–2022 · strength 0.74
- Paper Utilizing GCN and Meta-Learning Strategy in Unsupervised Domain Adaptation for Pancreatic Cancer Segmentation. DOI 10.1109/jbhi.2021.3085092↗
- Paper Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutat… DOI 10.1109/tmi.2020.3035789↗
- Paper Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation. DOI 10.1109/tmi.2021.3104460↗
- Weishen Wang · 3 shared papers, 2023–2026 · strength 0.72
- Paper A dual-transformation with contrastive learning framework for lymph node metastasis prediction in pancreatic cancer. DOI 10.1016/j.media.2023.102753↗
- Paper A clinician-centric intelligent method towards reliable pancreatic cancer vascular invasion assessment: a retrospective… DOI 10.1016/j.lanwpc.2026.101890↗
- Paper A deep-learning radiomics-based lymph node metastasis predictive model for pancreatic cancer: a diagnostic study. DOI 10.1097/js9.0000000000000469↗
- Jiaqi Qu · 2 shared papers, 2023–2024 · strength 0.62
- Yijue Zhang · 2 shared papers, 2023–2025 · strength 0.52
- Tao Chen · 2 shared papers, 2023 · strength 0.46
- Paper Causality-Driven Graph Neural Network for Early Diagnosis of Pancreatic Cancer in Non-Contrast Computerized Tomography. DOI 10.1109/tmi.2023.3236162↗
- Paper Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma. DOI 10.3389/fonc.2023.1074445↗
- Rui Guo · 1 shared paper, 2026 · strength 0.26
- Liu Y · 1 shared paper, 2026 · strength 0.26
- Shi‐Ting Feng · 1 shared paper, 2026 · strength 0.26
- Xinyue Li · 1 shared paper, 2023 · strength 0.24
- Yingbin Liu · 1 shared paper, 2023 · strength 0.22
- Xinsen Xu · 1 shared paper, 2023 · strength 0.22
- Ningzhen Fu · 1 shared paper, 2023 · strength 0.19
- Haoda Chen · 1 shared paper, 2023 · strength 0.19
- Baiyong Shen · 1 shared paper, 2023 · strength 0.19
- Fei Miao · 1 shared paper, 2021 · strength 0.14
- Jing Gao · 1 shared paper, 2021 · strength 0.14
- Biao Li · 1 shared paper, 2021 · strength 0.14
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.