Pujun Guan
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Biomaterials top 10%
- Nanoparticle-Based Drug Delivery
Papers in
-
- Lymphoma Diagnosis and Treatment 4
- Oncology 4
- Viral-associated cancers and disorders 4
- Co-authors
- Qiyong Gong (3 shared papers)Xiaoli Wei (2 shared papers)Kui Luo (2 shared papers)Hongyan Zhu (2 shared papers)Min Cong Wu (2 shared papers)Qiang Luo (2 shared papers)Ling Pan (5 shared papers)Ling Sun (1 shared paper)
- Journals
- The American Journal of Surgical Pathology (3 papers)Oncotarget (2 papers)ACS Applied Materials & Interfaces (2 papers)JCI Insight (1 paper)BMC Cancer (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Pujun Guan
24 papers receiving 921 citations
Pujun Guan's Hit Papers
Peers
Comparison fields: 5 of 95
- Health Informatics 257
- Biomaterials 103
- Health Information Management 37
- Hematology 51
- Drug Discovery 1
Countries citing papers authored by Pujun Guan
This map shows the geographic impact of Pujun Guan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pujun Guan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pujun Guan more than expected).
Fields of papers citing papers by Pujun Guan
This network shows the impact of papers produced by Pujun Guan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pujun Guan. The network helps show where Pujun Guan may publish in the future.
Co-authors
The 25 scholars most cited alongside Pujun Guan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI Hit paper breakdown → | 2022 | 410 |
| 2 | 2016 | 111 | |
| 3 | 2016 | 98 | |
| 4 | 2016 | 61 | |
| 5 | 2018 | 42 | |
| 6 | 2015 | 29 | |
| 7 | 2020 | 29 | |
| 8 | 2023 | 28 | |
| 9 | 2022 | 21 | |
| 10 | 2020 | 17 | |
| 11 | 2023 | 15 | |
| 12 | 2019 | 14 | |
| 13 | 2018 | 12 | |
| 14 | 2019 | 12 | |
| 15 | 2020 | 9 | |
| 16 | 2019 | 7 | |
| 17 | 2024 | 7 | |
| 18 | 2019 | 6 | |
| 19 | 2023 | 5 | |
| 20 | 2017 | 3 |
About Pujun Guan
Pujun Guan is a scholar working on Pathology and Forensic Medicine, Oncology, Immunology, Pulmonary and Respiratory Medicine and Polymers and Plastics, having authored 24 papers that have together received 943 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (4 papers), Viral-associated cancers and disorders (4 papers), Atherosclerosis and Cardiovascular Diseases (3 papers), Cholesterol and Lipid Metabolism (2 papers), Dendrimers and Hyperbranched Polymers (2 papers), Connective tissue disorders research (2 papers), Aortic Disease and Treatment Approaches (2 papers) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Health Informatics (257 citations), Biomaterials (103 citations), Health Information Management (37 citations), Hematology (51 citations) and Drug Discovery (1 citation). Pujun Guan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Qiyong Gong, Xiaoli Wei, Kui Luo, Hongyan Zhu, Min Cong Wu, Qiang Luo, Ling Pan, Ling Sun, Xue Li and Biao Dong. Their work appears in journals such as The American Journal of Surgical Pathology, Oncotarget, ACS Applied Materials & Interfaces, JCI Insight and BMC Cancer.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.