Shuai Ming
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Ophthalmology top 5%
- Retinal and Optic Conditions
- Ocular Diseases and Behçet’s Syndrome
- Retinal Diseases and Treatments
Papers in
-
- COVID-19 diagnosis using AI 3
- Radiomics and Machine Learning in Medical Imaging 3
-
- Retinal Diseases and Treatments 3
- Retinal and Optic Conditions 3
- Glaucoma and retinal disorders 2
- Co-authors
- Bo Lei (8 shared papers)Huijuan He (2 shared papers)Fanghong Chen (1 shared paper)Qiang Shen (1 shared paper)Ya Li (1 shared paper)Sijia Cui (2 shared papers)Xiangyang Gong (2 shared papers)Lei Bo (2 shared papers)
- Journals
- Scientific Reports (2 papers)BMJ Open (1 paper)JMIR Medical Education (1 paper)Pharmaceutics (1 paper)Journal of Medical Internet Research (1 paper)
- Partner nations
- ChinaNetherlandsSingapore
In The Last Decade
Shuai Ming
19 papers receiving 285 citations
Peers
Comparison fields: 5 of 67
- Health Informatics 35
- Ophthalmology 94
- Radiology, Nuclear Medicine and Imaging 122
- Health 19
- Rheumatology 28
Countries citing papers authored by Shuai Ming
This map shows the geographic impact of Shuai Ming'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 Shuai Ming with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuai Ming more than expected).
Fields of papers citing papers by Shuai Ming
This network shows the impact of papers produced by Shuai Ming. 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 Shuai Ming. The network helps show where Shuai Ming may publish in the future.
Co-authors
The 25 scholars most cited alongside Shuai Ming, 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 | 72 | |
| 2 | 2018 | 39 | |
| 3 | 2023 | 31 | |
| 4 | 2021 | 23 | |
| 5 | 2022 | 21 | |
| 6 | 2022 | 19 | |
| 7 | 2020 | 18 | |
| 8 | 2023 | 11 | |
| 9 | 2024 | 10 | |
| 10 | 2024 | 9 | |
| 11 | 2021 | 9 | |
| 12 | 2024 | 8 | |
| 13 | 2022 | 7 | |
| 14 | 2024 | 4 | |
| 15 | An analysis of AIDS projects funded by National Natural Science Foundation of China from 1999 to 2011 | 2013 | 2 |
| 16 | 2019 | 2 | |
| 17 | 2014 | 2 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 0 |
About Shuai Ming
Shuai Ming is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology, Molecular Biology, Pulmonary and Respiratory Medicine and Otorhinolaryngology, having authored 20 papers that have together received 289 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (3 papers), RNA Interference and Gene Delivery (3 papers), Retinal Diseases and Treatments (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Retinal and Optic Conditions (3 papers), Health Literacy and Information Accessibility (2 papers), Glaucoma and retinal disorders (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (35 citations), Ophthalmology (94 citations), Radiology, Nuclear Medicine and Imaging (122 citations), Health (19 citations) and Rheumatology (28 citations). Shuai Ming has collaborated with scholars based in China, Netherlands and Singapore. Frequent co-authors include Bo Lei, Huijuan He, Fanghong Chen, Qiang Shen, Ya Li, Sijia Cui, Xiangyang Gong, Lei Bo, Jie Han and Yan Liu. Their work appears in journals such as Scientific Reports, BMJ Open, JMIR Medical Education, Pharmaceutics and Journal of Medical Internet 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.