Dateng Li
Impact in
- Dermatology top 5%
- Dermatology and Skin Diseases
Papers in
-
- Statistical Methods in Clinical Trials 5
- Statistical Methods and Bayesian Inference 2
- Co-authors
- Bret J. Musser (2 shared papers)Gregory P. Geba (2 shared papers)Kusha A Mohammadi (3 shared papers)Marius Ardeleanu (1 shared paper)Jinteng Li (4 shared papers)Yunshu Che (3 shared papers)Zhongyu Xie (4 shared papers)Zepeng Su (4 shared papers)
- Journals
- Statistics in Medicine (4 papers)Cancer Management and Research (1 paper)Molecular Therapy — Nucleic Acids (1 paper)Journal of Biomechanics (1 paper)Prevention Science (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Dateng Li
19 papers receiving 273 citations
Peers
Comparison fields: 5 of 57
- Dermatology 59
- Immunology and Allergy 10
- Rheumatology 24
- Genetics 15
- Statistics and Probability 21
Countries citing papers authored by Dateng Li
This map shows the geographic impact of Dateng 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 Dateng Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dateng Li more than expected).
Fields of papers citing papers by Dateng Li
This network shows the impact of papers produced by Dateng 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 Dateng Li. The network helps show where Dateng Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Dateng 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 | 2022 | 76 | |
| 2 | 2023 | 60 | |
| 3 | 2022 | 24 | |
| 4 | 2020 | 21 | |
| 5 | 2023 | 19 | |
| 6 | 2022 | 16 | |
| 7 | 2020 | 14 | |
| 8 | 2023 | 11 | |
| 9 | 2019 | 6 | |
| 10 | 2019 | 6 | |
| 11 | 2022 | 5 | |
| 12 | 2024 | 4 | |
| 13 | 2023 | 3 | |
| 14 | 2025 | 3 | |
| 15 | 2022 | 2 | |
| 16 | 2022 | 2 | |
| 17 | 2018 | 1 | |
| 18 | 2020 | 1 | |
| 19 | 2023 | 1 |
About Dateng Li
Dateng Li is a scholar working on Statistics and Probability, Internal Medicine, Endocrine and Autonomic Systems, Molecular Medicine and Dermatology, having authored 19 papers that have together received 275 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (5 papers), Statistical Methods and Bayesian Inference (2 papers), Substance Abuse Treatment and Outcomes (2 papers), Dermatology and Skin Diseases (1 paper), Natural Compounds in Disease Treatment (1 paper), COVID-19 Clinical Research Studies (1 paper), Circadian rhythm and melatonin (1 paper) and Nanoparticle-Based Drug Delivery (1 paper). The work is most often cited by research in Dermatology (59 citations), Immunology and Allergy (10 citations), Rheumatology (24 citations), Genetics (15 citations) and Statistics and Probability (21 citations). Dateng Li has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Bret J. Musser, Gregory P. Geba, Kusha A Mohammadi, Marius Ardeleanu, Jinteng Li, Yunshu Che, Zhongyu Xie, Zepeng Su, Wenhui Yu and Jiajie Lin. Their work appears in journals such as Statistics in Medicine, Cancer Management and Research, Molecular Therapy — Nucleic Acids, Journal of Biomechanics and Prevention Science.
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.