Dingwen Li
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Cardiac, Anesthesia and Surgical Outcomes
Papers in
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- Frailty in Older Adults 2
- Co-authors
- Chenyang LuChristopher R. KingMichael S. AvidanThomas KannampallilTroy S. WildesBing XueJoanna AbrahamKai Gao
- Journals
- Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (1 paper)JAMA Network Open (1 paper)Computers and Electronics in Agriculture (1 paper)HPB (1 paper)Journal of Medical Internet Research (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Dingwen Li
16 papers receiving 376 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Health Informatics 62
- Cardiology and Cardiovascular Medicine 102
- Critical Care and Intensive Care Medicine 19
- Anesthesiology and Pain Medicine 18
- Geriatrics and Gerontology 9
Countries citing papers authored by Dingwen Li
This map shows the geographic impact of Dingwen Li'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 Dingwen Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dingwen Li more than expected).
Fields of papers citing papers by Dingwen Li
This network shows the impact of papers produced by Dingwen Li. 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 Dingwen Li. The network helps show where Dingwen Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Dingwen Li, 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 | 2024 | 1 | |
| 2 | 2023 | 15 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 74 | |
| 5 | 2022 | 1 | |
| 6 | 2022 | 5 | |
| 7 | 2022 | 2 | |
| 8 | 2022 | 7 | |
| 9 | 2021 | 40 | |
| 10 | Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications Hit paper breakdown → | 2021 | 190 |
| 11 | 2021 | 10 | |
| 12 | 2020 | 12 | |
| 13 | 2020 | 13 | |
| 14 | 2020 | 9 | |
| 15 | 2015 | 1 | |
| 16 | Study on the antineoplastic effect of caulis spatholobi extracts | 2009 | 1 |
About Dingwen Li
Dingwen Li is a scholar working on Health Informatics, Geriatrics and Gerontology, Family Practice, Artificial Intelligence and Signal Processing, having authored 16 papers that have together received 384 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (6 papers), Sepsis Diagnosis and Treatment (3 papers), Frailty in Older Adults (2 papers), Time Series Analysis and Forecasting (2 papers), Hip and Femur Fractures (2 papers), Advanced Neural Network Applications (2 papers), Pancreatic and Hepatic Oncology Research (2 papers) and Cardiac, Anesthesia and Surgical Outcomes (2 papers). The work is most often cited by research in Health Informatics (62 citations), Cardiology and Cardiovascular Medicine (102 citations), Critical Care and Intensive Care Medicine (19 citations), Anesthesiology and Pain Medicine (18 citations) and Geriatrics and Gerontology (9 citations). Dingwen Li has collaborated with scholars based in United States and China. Frequent co-authors include Chenyang Lu, Christopher R. King, Michael S. Avidan, Thomas Kannampallil, Troy S. Wildes, Bing Xue, Joanna Abraham, Kai Gao, Wenjie Yang and Ronghua Du. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, JAMA Network Open, Computers and Electronics in Agriculture, HPB 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.