ResearcherShanghai Jiao Tong UniversityNo recent work listed
Xiaozhu Lin
Matched on ORCID iD 0000-0002-8195-3932; OpenAlex author ID A5010794546. Sources: OpenAlex.
Their work
- Papers
- 12 (first author 1, last author 3)
- Trials
- 0
- Grants
- 0
- Labs led
- 1
- Collaborators
- 22
2011: 1 paper · 2012: none · 2013: none · 2014: none · 2015: none · 2016: none · 2017: none · 2018: none · 2019: none · 2020: 2 papers · 2021: 3 papers · 2022: 3 papers · 2023: 3 papers
Papers 12
- Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features derived from 18F-FDG PET and MRI. Co-author DOI 10.1016/j.crad.2023.06.011↗
- LIPH contributes to glycolytic phenotype in pancreatic ductal adenocarcinoma by activating LPA/LPAR axis and maintaining ALDOA stability. Co-author DOI 10.1186/s12967-023-04702-6↗
- The value of 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance whole-body scans and local enhancement scans in the preoperative staging an… Last author DOI 10.21037/qims-22-731↗
- Utilizing GCN and Meta-Learning Strategy in Unsupervised Domain Adaptation for Pancreatic Cancer Segmentation. Co-author DOI 10.1109/jbhi.2021.3085092↗
- Model-Driven Deep Learning Method for Pancreatic Cancer Segmentation Based on Spiral-Transformation. Co-author DOI 10.1109/tmi.2021.3104460↗
- Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features derived from 18F-FDG PET/MR imaging Co-author DOI 10.21203/rs.3.rs-2040971/v1↗
- Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutation in Pancreatic Cancer. First author DOI 10.1109/tmi.2020.3035789↗
- Joint Radiomics Analysis on 18F-FDG-PET-MRI of Primary Tumor to Predict the Risk of Synchronous Distant Metastasis in Pancreatic Ductal Adenocarcinoma Co-author DOI 10.21203/rs.3.rs-801341/v1↗
- Differentiating TP53 Mutation Status in Pancreatic Ductal Adenocarcinoma Using Multiparametric MRI-Derived Radiomics. Last author DOI 10.3389/fonc.2021.632130↗
- Resectable pancreatic ductal adenocarcinoma: association between preoperative CT texture features and metastatic nodal involvement. Last author DOI 10.1186/s40644-020-0296-3↗
- Performance of Multiparametric Functional Imaging and Texture Analysis in Predicting Synchronous Metastatic Disease in Pancreatic Ductal Adenocarcinoma Patient… Co-author DOI 10.3389/fonc.2020.00198↗
- Differentiating pancreatic ductal adenocarcinoma from pancreatic serous cystadenoma, mucinous cystadenoma, and a pseudocyst with detailed analysis of cystic fe… Co-author DOI 10.3348/kjr.2011.12.2.187↗
Closest collaborators
The 22 strongest of 22 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Biao Li · 6 shared papers, 2020–2023 · strength 0.91
- Paper The value of 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance whole-body scans and local enhancem… DOI 10.21037/qims-22-731↗
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.1016/j.crad.2023.06.011↗
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.21203/rs.3.rs-2040971/v1↗
- Xiaohua Qian · 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↗
- Fei Miao · 5 shared papers, 2020–2023 · strength 0.72
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.1016/j.crad.2023.06.011↗
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.21203/rs.3.rs-2040971/v1↗
- Paper Differentiating TP53 Mutation Status in Pancreatic Ductal Adenocarcinoma Using Multiparametric MRI-Derived Radiomics. DOI 10.3389/fonc.2021.632130↗
- Jing Gao · 5 shared papers, 2020–2023 · strength 0.72
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.1016/j.crad.2023.06.011↗
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.21203/rs.3.rs-2040971/v1↗
- Paper Differentiating TP53 Mutation Status in Pancreatic Ductal Adenocarcinoma Using Multiparametric MRI-Derived Radiomics. DOI 10.3389/fonc.2021.632130↗
- Xiahan Chen · 3 shared papers, 2021–2022 · strength 0.52
- 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↗
- Paper Differentiating TP53 Mutation Status in Pancreatic Ductal Adenocarcinoma Using Multiparametric MRI-Derived Radiomics. DOI 10.3389/fonc.2021.632130↗
- Kuangyu Shi · 3 shared papers, 2021–2023 · strength 0.46
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.1016/j.crad.2023.06.011↗
- Paper Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features d… DOI 10.21203/rs.3.rs-2040971/v1↗
- Paper Joint Radiomics Analysis on 18F-FDG-PET-MRI of Primary Tumor to Predict the Risk of Synchronous Distant Metastasis in P… DOI 10.21203/rs.3.rs-801341/v1↗
- Jun Li · 2 shared papers, 2022 · strength 0.41
- Weishen Wang · 1 shared paper, 2023 · strength 0.18
- Baiyong Shen · 1 shared paper, 2023 · strength 0.18
- Yongrui Bai · 1 shared paper, 2023 · strength 0.18
- Cheng Xiong · 1 shared paper, 2023 · strength 0.16
- Ting Wang · 1 shared paper, 2023 · strength 0.16
- Zhichong Wu · 1 shared paper, 2023 · strength 0.16
- Lingxi Jiang · 1 shared paper, 2023 · strength 0.16
- Youwei Zhu · 1 shared paper, 2023 · strength 0.16
- Lijie Han · 1 shared paper, 2023 · strength 0.16
- Meilin Xue · 1 shared paper, 2023 · strength 0.16
- Hao Chen · 1 shared paper, 2023 · strength 0.16
- Baiyong Shen · 1 shared paper, 2023 · strength 0.16
- Wei Fang · 1 shared paper, 2020 · strength 0.13
- Peijie Lyu · 1 shared paper, 2011 · strength 0.03
- Jing Xie · 1 shared paper, 2011 · strength 0.03
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.