Huijing Ma
Impact in
-
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
-
- Ultrasound in Clinical Applications
Papers in
-
- Birth, Development, and Health 4
- Co-authors
- Jianbo Shao (6 shared papers)Hui Li (3 shared papers)Xi Zhou (2 shared papers)Luke Wesemann (3 shared papers)Jun Xia (2 shared papers)Jiani Hu (1 shared paper)Wei Chen (2 shared papers)Rafael Ramos (1 shared paper)
- Journals
- Bioscience Reports (1 paper)Gene (1 paper)Materials Science and Engineering C (1 paper)Journal of Hypertension (1 paper)Food Chemistry (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Huijing Ma
18 papers receiving 290 citations
Peers
Comparison fields: 5 of 89
- Infectious Diseases 106
- Critical Care and Intensive Care Medicine 29
- Obstetrics and Gynecology 38
- Health Informatics 4
- Biochemistry 11
Countries citing papers authored by Huijing Ma
This map shows the geographic impact of Huijing Ma'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 Huijing Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huijing Ma more than expected).
Fields of papers citing papers by Huijing Ma
This network shows the impact of papers produced by Huijing Ma. 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 Huijing Ma. The network helps show where Huijing Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Huijing Ma, 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 | 2020 | 95 | |
| 2 | 2022 | 40 | |
| 3 | 2022 | 33 | |
| 4 | 2012 | 23 | |
| 5 | 2021 | 19 | |
| 6 | 2020 | 16 | |
| 7 | 2021 | 15 | |
| 8 | 2020 | 13 | |
| 9 | 2021 | 10 | |
| 10 | 2021 | 9 | |
| 11 | 2024 | 6 | |
| 12 | 2015 | 4 | |
| 13 | 2024 | 3 | |
| 14 | 2020 | 2 | |
| 15 | 2024 | 2 | |
| 16 | 2020 | 2 | |
| 17 | 2025 | 1 | |
| 18 | 2024 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2024 | 0 |
About Huijing Ma
Huijing Ma is a scholar working on Molecular Biology, Pediatrics, Perinatology and Child Health, Obstetrics and Gynecology, Infectious Diseases and Surgery, having authored 20 papers that have together received 294 indexed citations. Recurring topics across this work include Birth, Development, and Health (4 papers), Pregnancy and preeclampsia studies (4 papers), COVID-19 diagnosis using AI (2 papers), Tissue Engineering and Regenerative Medicine (2 papers), Cancer Cells and Metastasis (2 papers), COVID-19 Clinical Research Studies (2 papers), Lung Cancer Diagnosis and Treatment (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Infectious Diseases (106 citations), Critical Care and Intensive Care Medicine (29 citations), Obstetrics and Gynecology (38 citations), Health Informatics (4 citations) and Biochemistry (11 citations). Huijing Ma has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Jianbo Shao, Hui Li, Xi Zhou, Luke Wesemann, Jun Xia, Jiani Hu, Wei Chen, Rafael Ramos, Jie Tian and Haikuan Wang. Their work appears in journals such as Bioscience Reports, Gene, Materials Science and Engineering C, Journal of Hypertension and Food Chemistry.
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.