Dai Su
Impact in
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- Aging and Gerontology Research
- Health top 10%
- Health disparities and outcomes
Papers in
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- Advanced machining processes and optimization 4
- Gear and Bearing Dynamics Analysis 4
- Lubricants and Their Additives 3
- Finance 7
- Healthcare Systems and Reforms 7
- Co-authors
- Yingchun Chen (21 shared papers)Xingyu Zhang (4 shared papers)Kevin He (4 shared papers)Min Tan (8 shared papers)Xinlin Chen (4 shared papers)Jingjing Chang (14 shared papers)Yunfan Zhang (3 shared papers)Haomiao Li (15 shared papers)
- Journals
- International Journal of Environmental Research and Public Health (6 papers)BMC Health Services Research (3 papers)Frontiers in Public Health (2 papers)BMC Public Health (2 papers)BMJ Open (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Dai Su
48 papers receiving 533 citations
Peers
Comparison fields: 5 of 109
- Neuropsychology and Physiological Psychology 19
- Health 49
- Finance 56
- Geriatrics and Gerontology 10
- Transportation 18
Countries citing papers authored by Dai Su
This map shows the geographic impact of Dai Su'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 Dai Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dai Su more than expected).
Fields of papers citing papers by Dai Su
This network shows the impact of papers produced by Dai Su. 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 Dai Su. The network helps show where Dai Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Dai Su, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 94 | |
| 2 | 2022 | 57 | |
| 3 | 2019 | 40 | |
| 4 | 2020 | 40 | |
| 5 | 2019 | 33 | |
| 6 | 2013 | 32 | |
| 7 | 2021 | 23 | |
| 8 | 2022 | 18 | |
| 9 | 2023 | 16 | |
| 10 | 2018 | 13 | |
| 11 | 2013 | 12 | |
| 12 | 2019 | 11 | |
| 13 | 2020 | 10 | |
| 14 | 2022 | 10 | |
| 15 | 2013 | 10 | |
| 16 | 2018 | 7 | |
| 17 | 2022 | 7 | |
| 18 | 2019 | 7 | |
| 19 | 2019 | 6 | |
| 20 | 2019 | 6 |
About Dai Su
Dai Su is a scholar working on Mechanical Engineering, Finance, Industrial and Manufacturing Engineering, General Health Professions and Control and Systems Engineering, having authored 49 papers that have together received 540 indexed citations. Recurring topics across this work include Healthcare Systems and Reforms (7 papers), Advanced machining processes and optimization (4 papers), Gear and Bearing Dynamics Analysis (4 papers), Lubricants and Their Additives (3 papers), Healthcare Policy and Management (3 papers), Health disparities and outcomes (3 papers), Intergenerational Family Dynamics and Caregiving (3 papers) and Tribology and Wear Analysis (3 papers). The work is most often cited by research in Neuropsychology and Physiological Psychology (19 citations), Health (49 citations), Finance (56 citations), Geriatrics and Gerontology (10 citations) and Transportation (18 citations). Dai Su has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yingchun Chen, Xingyu Zhang, Kevin He, Min Tan, Xinlin Chen, Jingjing Chang, Yunfan Zhang, Haomiao Li, Amin Al‐Habaibeh and Di Jiang. Their work appears in journals such as International Journal of Environmental Research and Public Health, BMC Health Services Research, Frontiers in Public Health, BMC Public Health and BMJ Open.
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.