ResearcherUniversity of PittsburghNo recent work listed
Hao Liu
Matched on ORCID iD 0000-0002-0237-2735; OpenAlex author ID A5100458775. Sources: OpenAlex.
Their work
- Papers
- 7 (first author 0, last author 1)
- Trials
- 0
- Grants
- 0
- Labs led
- 0
- Collaborators
- 23
2013: 1 paper · 2014: none · 2015: none · 2016: 1 paper · 2017: none · 2018: none · 2019: 1 paper · 2020: none · 2021: none · 2022: 2 papers · 2023: 2 papers
Papers 7
- Peritumoral and Intratumoral Texture Features Based on Multiparametric MRI and Multiple Machine Learning Methods to Preoperatively Evaluate the Pathological Ou… Co-author DOI 10.1002/jmri.28538↗
- Preoperative Extrapancreatic Extension Prediction in Patients with Pancreatic Cancer Using Multiparameter MRI and Machine Learning-Based Radiomics Model. Co-author DOI 10.1016/j.acra.2022.09.017↗
- Adaptive Dynamic Therapy and Survivorship for Operable Pancreatic Cancer. Co-author DOI 10.1001/jamanetworkopen.2022.18355↗
- ETV4 promotes pancreatic ductal adenocarcinoma metastasis through activation of the CXCL13/CXCR5 signaling axis. Co-author DOI 10.1016/j.canlet.2021.09.026↗
- Development of a Tumor-Responsive Nanopolyplex Targeting Pancreatic Cancer Cells and Stroma. Co-author DOI 10.1021/acsami.9b15116↗
- Neoadjuvant Gemcitabine Chemotherapy followed by Concurrent IMRT Simultaneous Boost Achieves High R0 Resection in Borderline Resectable Pancreatic Cancer Patie… Last author DOI 10.1371/journal.pone.0166606↗
- [Analysis of the relationship between clinicopathological factors and lymph node matastasis of pancreatic adenocarcinoma]. Co-author DOI 10.3760/cma.j.issn.0253-3766.2013.02.012↗
Closest collaborators
The 23 strongest of 23 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Ni Xie · 2 shared papers, 2023 · strength 0.36
- Paper Preoperative Extrapancreatic Extension Prediction in Patients with Pancreatic Cancer Using Multiparameter MRI and Machi… DOI 10.1016/j.acra.2022.09.017↗
- Paper Peritumoral and Intratumoral Texture Features Based on Multiparametric MRI and Multiple Machine Learning Methods to Pre… DOI 10.1002/jmri.28538↗
- Xuhui Fan · 2 shared papers, 2023 · strength 0.36
- Paper Preoperative Extrapancreatic Extension Prediction in Patients with Pancreatic Cancer Using Multiparameter MRI and Machi… DOI 10.1016/j.acra.2022.09.017↗
- Paper Peritumoral and Intratumoral Texture Features Based on Multiparametric MRI and Multiple Machine Learning Methods to Pre… DOI 10.1002/jmri.28538↗
- Baiwen Li · 2 shared papers, 2023 · strength 0.36
- Paper Preoperative Extrapancreatic Extension Prediction in Patients with Pancreatic Cancer Using Multiparameter MRI and Machi… DOI 10.1016/j.acra.2022.09.017↗
- Paper Peritumoral and Intratumoral Texture Features Based on Multiparametric MRI and Multiple Machine Learning Methods to Pre… DOI 10.1002/jmri.28538↗
- Lanting Yu · 1 shared paper, 2023 · strength 0.18
- Han Wang · 1 shared paper, 2023 · strength 0.18
- Melissa Ellen Hogg · 1 shared paper, 2022 · strength 0.14
- Amer H. Zureikat · 1 shared paper, 2022 · strength 0.14
- Samer S. AlMasri · 1 shared paper, 2022 · strength 0.14
- Ibrahim Nassour · 1 shared paper, 2022 · strength 0.14
- Herbert J. Zeh · 1 shared paper, 2022 · strength 0.14
- Nathan Bahary · 1 shared paper, 2022 · strength 0.14
- Brian A. Boone · 1 shared paper, 2022 · strength 0.14
- Aatur Dilip Singhi · 1 shared paper, 2022 · strength 0.14
- Alessandro Paniccia · 1 shared paper, 2022 · strength 0.14
- Daiming Fan · 1 shared paper, 2022 · strength 0.13
- Xiaoliang Gao · 1 shared paper, 2022 · strength 0.13
- Weijie Wang · 1 shared paper, 2022 · strength 0.13
- Yuanke Li · 1 shared paper, 2019 · strength 0.11
- Kun Cheng · 1 shared paper, 2019 · strength 0.11
- Xiaolun Huang · 1 shared paper, 2016 · strength 0.06
- Ping Zhao · 1 shared paper, 2013 · strength 0.04
- Jiangjiao Zhou · 1 shared paper, 2013 · strength 0.04
- Chengfeng Wang · 1 shared paper, 2013 · strength 0.04
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.