Ling Feng
Impact in
- Obstetrics and Gynecology top 0.2%
- COVID-19 Impact on Reproduction
- Pregnancy and preeclampsia studies
- Gestational Diabetes Research and Management
- Modeling and Simulation top 2%
Papers in
-
- Pregnancy and preeclampsia studies 25
- Gestational Diabetes Research and Management 17
- COVID-19 Impact on Reproduction 10
- Maternal and Perinatal Health Interventions 9
-
- COVID-19 epidemiological studies 10
Ling Feng
146 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Obstetrics and Gynecology 1.5k
- Modeling and Simulation 171
- Pediatrics, Perinatology and Child Health 688
- Infectious Diseases 609
- Public Health, Environmental and Occupational Health 699
Countries citing papers authored by Ling Feng
This map shows the geographic impact of Ling Feng'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 Ling Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Feng more than expected).
Fields of papers citing papers by Ling Feng
This network shows the impact of papers produced by Ling Feng. 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 Ling Feng. The network helps show where Ling Feng may publish in the future.
Co-authors
The 25 scholars most cited alongside Ling Feng, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 3 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 8 | |
| 6 | 2023 | 6 | |
| 7 | 2023 | 3 | |
| 8 | 2023 | 8 | |
| 9 | 2023 | 0 | |
| 10 | 2023 | 1 | |
| 11 | 2022 | 2 | |
| 12 | 2021 | 14 | |
| 13 | 2021 | 4 | |
| 14 | Epidemiological and clinical findings of discharge patients infected with the 2019 novel coronavirus (SARS-COV-2) in Changchun, Northeast China: A retrospective cohort study | 2021 | 2 |
| 15 | 2021 | 13 | |
| 16 | 2020 | 17 | |
| 17 | 2020 | 20 | |
| 18 | 2020 | 9 | |
| 19 | 2016 | 22 | |
| 20 | [Epidemiological investigation on an outbreak of severe fever with thrombocytopenia syndrome in northwest Zhejiang province]. | 2015 | 8 |
About Ling Feng
Ling Feng is a scholar working on Obstetrics and Gynecology, Modeling and Simulation, Infectious Diseases, Pediatrics, Perinatology and Child Health and Public Health, Environmental and Occupational Health, having authored 153 papers that have together received 3.3k indexed citations. Recurring topics across this work include Pregnancy and preeclampsia studies (25 papers), Viral Infections and Vectors (20 papers), Gestational Diabetes Research and Management (17 papers), COVID-19 Impact on Reproduction (10 papers), Birth, Development, and Health (10 papers), COVID-19 epidemiological studies (10 papers), Maternal and Perinatal Health Interventions (9 papers) and Mosquito-borne diseases and control (9 papers). The work is most often cited by research in Obstetrics and Gynecology (1.5k citations), Modeling and Simulation (171 citations), Pediatrics, Perinatology and Child Health (688 citations), Infectious Diseases (609 citations) and Public Health, Environmental and Occupational Health (699 citations). Ling Feng has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Shaoshuai Wang, Juan Gui, Weiyong Liu, Yong Cao, Lili Guo, Ling Chen, Wanjiang Zeng, Qing Liu, Dongrui Deng and Jianli Wu. Their work appears in journals such as Placenta, BMC Infectious Diseases, PLoS ONE, Journal of Zhejiang University SCIENCE B and Frontiers in Public Health.
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.