Weishun Lan
Impact in
- Obstetrics and Gynecology top 2%
- COVID-19 Impact on Reproduction
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
Papers in
-
- COVID-19 Impact on Reproduction 4
- Gynecological conditions and treatments 1
-
- Long-Term Effects of COVID-19 2
- Co-authors
- Jinning Li (5 shared papers)Dengbin Wang (4 shared papers)Huanhuan Liu (3 shared papers)Fang Liu (1 shared paper)Tingting Zhang (1 shared paper)Xufeng Wu (3 shared papers)Tingting Zhang (2 shared papers)Hu Shan (1 shared paper)
- Journals
- Journal of Infection (2 papers)Heliyon (1 paper)Infection and Drug Resistance (1 paper)International Journal of Gynecology & Obstetrics (1 paper)Frontiers in Microbiology (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Weishun Lan
13 papers receiving 547 citations
Weishun Lan's Hit Papers
Peers
Comparison fields: 5 of 56
- Obstetrics and Gynecology 219
- Infectious Diseases 156
- Critical Care and Intensive Care Medicine 23
- Health Informatics 7
- Radiology, Nuclear Medicine and Imaging 106
Countries citing papers authored by Weishun Lan
This map shows the geographic impact of Weishun Lan'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 Weishun Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weishun Lan more than expected).
Fields of papers citing papers by Weishun Lan
This network shows the impact of papers produced by Weishun Lan. 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 Weishun Lan. The network helps show where Weishun Lan may publish in the future.
Co-authors
The 25 scholars most cited alongside Weishun Lan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Clinical and CT imaging features of the COVID-19 pneumonia: Focus on pregnant women and children Hit paper breakdown → | 2020 | 356 |
| 2 | 2020 | 58 | |
| 3 | 2020 | 35 | |
| 4 | 2013 | 28 | |
| 5 | 2020 | 23 | |
| 6 | 2016 | 23 | |
| 7 | 2022 | 12 | |
| 8 | 2020 | 9 | |
| 9 | 2023 | 7 | |
| 10 | COVID-19肺炎の臨床およびCT画像特徴:妊婦および小児に焦点を当てて【JST・京大機械翻訳】 | 2020 | 6 |
| 11 | 2020 | 2 | |
| 12 | 2022 | 2 | |
| 13 | 2021 | 1 |
About Weishun Lan
Weishun Lan is a scholar working on Obstetrics and Gynecology, Neurology, Oncology, Public Health, Environmental and Occupational Health and Radiology, Nuclear Medicine and Imaging, having authored 13 papers that have together received 562 indexed citations. Recurring topics across this work include COVID-19 Impact on Reproduction (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Long-Term Effects of COVID-19 (2 papers), COVID-19 and healthcare impacts (2 papers), COVID-19 diagnosis using AI (2 papers), Ectopic Pregnancy Diagnosis and Management (2 papers), Artificial Intelligence in Healthcare and Education (1 paper) and Gynecological conditions and treatments (1 paper). The work is most often cited by research in Obstetrics and Gynecology (219 citations), Infectious Diseases (156 citations), Critical Care and Intensive Care Medicine (23 citations), Health Informatics (7 citations) and Radiology, Nuclear Medicine and Imaging (106 citations). Weishun Lan has collaborated with scholars based in China and United States. Frequent co-authors include Jinning Li, Dengbin Wang, Huanhuan Liu, Fang Liu, Tingting Zhang, Xufeng Wu, Tingting Zhang, Fang Liu, Hu Shan and Liang Wang. Their work appears in journals such as Journal of Infection, Heliyon, Infection and Drug Resistance, International Journal of Gynecology & Obstetrics and Frontiers in Microbiology.
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.