Hong Pu
Impact in
- Obstetrics and Gynecology top 10%
- Endometrial and Cervical Cancer Treatments
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 6
- MRI in cancer diagnosis 4
- COVID-19 diagnosis using AI 3
- Oncology 10
- Colorectal Cancer Surgical Treatments 9
- Co-authors
- Hang Li (11 shared papers)Long-Lin Yin (9 shared papers)Zhenlin Li (7 shared papers)Yuting Wang (6 shared papers)Guangwen Chen (5 shared papers)Tong Zheng (4 shared papers)Minghui Pang (5 shared papers)Aimin Yang (4 shared papers)
- Journals
- European Radiology (4 papers)BMC Gastroenterology (4 papers)Frontiers in Oncology (2 papers)Computers in Biology and Medicine (2 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Hong Pu
47 papers receiving 519 citations
Peers
Comparison fields: 5 of 83
- Obstetrics and Gynecology 54
- Radiology, Nuclear Medicine and Imaging 123
- Internal Medicine 10
- Oncology 74
- Pulmonary and Respiratory Medicine 78
Countries citing papers authored by Hong Pu
This map shows the geographic impact of Hong Pu'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 Hong Pu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong Pu more than expected).
Fields of papers citing papers by Hong Pu
This network shows the impact of papers produced by Hong Pu. 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 Hong Pu. The network helps show where Hong Pu may publish in the future.
Co-authors
The 25 scholars most cited alongside Hong Pu, 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 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 57 | |
| 2 | 2021 | 32 | |
| 3 | 2023 | 31 | |
| 4 | 2016 | 30 | |
| 5 | 2015 | 29 | |
| 6 | 2018 | 24 | |
| 7 | 2022 | 22 | |
| 8 | 2013 | 20 | |
| 9 | 2019 | 20 | |
| 10 | 2014 | 19 | |
| 11 | 2017 | 16 | |
| 12 | 2019 | 15 | |
| 13 | 2019 | 14 | |
| 14 | 2022 | 13 | |
| 15 | 2020 | 12 | |
| 16 | 2020 | 12 | |
| 17 | 2019 | 12 | |
| 18 | 2021 | 12 | |
| 19 | 2024 | 10 | |
| 20 | 2020 | 10 |
About Hong Pu
Hong Pu is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology, Pulmonary and Respiratory Medicine, Biomedical Engineering and Health, Toxicology and Mutagenesis, having authored 50 papers that have together received 525 indexed citations. Recurring topics across this work include Colorectal Cancer Surgical Treatments (9 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Gastric Cancer Management and Outcomes (5 papers), Advanced X-ray and CT Imaging (4 papers), MRI in cancer diagnosis (4 papers), COVID-19 diagnosis using AI (3 papers), Endometrial and Cervical Cancer Treatments (3 papers) and Heavy Metal Exposure and Toxicity (3 papers). The work is most often cited by research in Obstetrics and Gynecology (54 citations), Radiology, Nuclear Medicine and Imaging (123 citations), Internal Medicine (10 citations), Oncology (74 citations) and Pulmonary and Respiratory Medicine (78 citations). Hong Pu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Hang Li, Long-Lin Yin, Zhenlin Li, Yuting Wang, Guangwen Chen, Tong Zheng, Minghui Pang, Aimin Yang, Ning Cheng and Yingchun Li. Their work appears in journals such as European Radiology, BMC Gastroenterology, Frontiers in Oncology, Computers in Biology and Medicine and Scientific Reports.
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.