Lan Dong
Impact in
- Obstetrics and Gynecology top 0.5%
- COVID-19 Impact on Reproduction
- Pregnancy and preeclampsia studies
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
Papers in
-
- COVID-19 Impact on Reproduction 3
- Endometrial and Cervical Cancer Treatments 1
- Gynecological conditions and treatments 1
-
- Pregnancy-related medical research 1
- Co-authors
- Jing Yang (3 shared papers)Songming He (1 shared paper)Chen Liu (1 shared paper)Jinhua Tian (1 shared paper)Jian Wang (1 shared paper)Chuchao Zhu (1 shared paper)Cheng Peng (1 shared paper)Xiaoqi Pan (1 shared paper)
In The Last Decade
Lan Dong
9 papers receiving 975 citations
Lan Dong's Hit Papers
Peers
Comparison fields: 5 of 67
- Obstetrics and Gynecology 783
- Infectious Diseases 182
- Pediatrics, Perinatology and Child Health 151
- Public Health, Environmental and Occupational Health 222
- Modeling and Simulation 25
Countries citing papers authored by Lan Dong
This map shows the geographic impact of Lan Dong'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 Lan Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lan Dong more than expected).
Fields of papers citing papers by Lan Dong
This network shows the impact of papers produced by Lan Dong. 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 Lan Dong. The network helps show where Lan Dong may publish in the future.
Co-authors
The 25 scholars most cited alongside Lan Dong, 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 | Possible Vertical Transmission of SARS-CoV-2 From an Infected Mother to Her Newborn Hit paper breakdown → | 2020 | 841 |
| 2 | 2020 | 54 | |
| 3 | 2020 | 49 | |
| 4 | 2020 | 30 | |
| 5 | 2020 | 16 | |
| 6 | 2020 | 11 | |
| 7 | 2024 | 5 | |
| 8 | 2016 | 4 | |
| 9 | Mesenchymal stem cell-derived exosomes ameliorate TGF-β1-induced endometrial fibrosis by altering their miRNA profile. | 2023 | 2 |
About Lan Dong
Lan Dong is a scholar working on Obstetrics and Gynecology, Public Health, Environmental and Occupational Health, Infectious Diseases, Urology and Clinical Psychology, having authored 9 papers that have together received 1.0k indexed citations. Recurring topics across this work include COVID-19 Impact on Reproduction (3 papers), Endometrial and Cervical Cancer Treatments (1 paper), Endometriosis Research and Treatment (1 paper), Pharmacological Effects of Natural Compounds (1 paper), Digital Imaging for Blood Diseases (1 paper), Pregnancy-related medical research (1 paper), Gynecological conditions and treatments (1 paper) and COVID-19 and healthcare impacts (1 paper). The work is most often cited by research in Obstetrics and Gynecology (783 citations), Infectious Diseases (182 citations), Pediatrics, Perinatology and Child Health (151 citations), Public Health, Environmental and Occupational Health (222 citations) and Modeling and Simulation (25 citations). Lan Dong has collaborated with scholars based in China, Australia and Thailand. Frequent co-authors include Jing Yang, Songming He, Chen Liu, Jinhua Tian, Jian Wang, Chuchao Zhu, Cheng Peng, Xiaoqi Pan, Lian Yang and Dayi Chen. Their work appears in journals such as BMC Pregnancy and Childbirth, Microscopy Research and Technique, Journal of Cellular and Molecular Medicine, JAMA and Virus Research.
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.