Dehan Kong
- Statistics and Probability top 2%
- Statistical Methods and Inference 13
- Statistical Methods and Bayesian Inference 7
- Advanced Causal Inference Techniques 5
- Computational Mathematics top 10%
- Health Informatics top 5%
- Rheumatology top 10%
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- Muscle metabolism and nutrition 9
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- Functional Brain Connectivity Studies 8
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- Nutritional Studies and Diet 6
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- Alzheimer's disease research and treatments 5
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- Dementia and Cognitive Impairment Research 5
- Co-authors
- Hongtu ZhuHao Helen ZhangFang YaoJoseph G. IbrahimPascal N. TyrrellAlan R. MoodyIndranil BalkiAnne L. Martel
- Journals
- American Journal of Clinical Nutrition (6 papers)Biometrika (4 papers)Journal of the American Statistical Association (4 papers)
- Partner nations
- CanadaUnited StatesChina
In The Last Decade
Dehan Kong
46 papers receiving 897 citations
Peers
Comparison fields: 5 of 144
- Statistics and Probability 259
- Computational Mathematics 17
- Health Informatics 30
- Rheumatology 120
- Cell Biology 107
Countries citing papers authored by Dehan Kong
This map shows the geographic impact of Dehan Kong'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 Dehan Kong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dehan Kong more than expected).
Fields of papers citing papers by Dehan Kong
This network shows the impact of papers produced by Dehan Kong. 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 Dehan Kong. The network helps show where Dehan Kong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dehan Kong, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 3 | |
| 9 | 2023 | 3 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 0 | |
| 12 | 2021 | 3 | |
| 13 | 2021 | 15 | |
| 14 | 2021 | 31 | |
| 15 | 2021 | 4 | |
| 16 | 2020 | 42 | |
| 17 | Multi-cause causal inference with unmeasured confounding and binary outcome | 2019 | 2 |
| 18 | Outlier Detection and Robust Estimation in Nonparametric Regression | 2018 | 2 |
| 19 | Single-nucleotide polymorphisms are associated with cognitive decline at Alzheimer's disease conversion within mild cognitive impairment patients | 2017 | 2 |
| 20 | 2015 | 32 |
About Dehan Kong
Dehan Kong is a scholar working on Statistics and Probability, Health Informatics and Cell Biology, having authored 56 papers that have together received 915 indexed citations. Recurring topics across this work include Statistical Methods and Inference (13 papers), Muscle metabolism and nutrition (9 papers), Functional Brain Connectivity Studies (8 papers), Statistical Methods and Bayesian Inference (7 papers), Nutritional Studies and Diet (6 papers), Advanced Causal Inference Techniques (5 papers), Alzheimer's disease research and treatments (5 papers) and Dementia and Cognitive Impairment Research (5 papers). The work is most often cited by research in Statistics and Probability (259 citations), Computational Mathematics (17 citations) and Health Informatics (30 citations). Dehan Kong has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Hongtu Zhu, Hao Helen Zhang, Fang Yao, Joseph G. Ibrahim, Pascal N. Tyrrell, Alan R. Moody, Indranil Balki, Anne L. Martel, Blaž Meden and Jacob Levman. Their work appears in journals such as American Journal of Clinical Nutrition, Biometrika, Journal of the American Statistical Association, Biometrics and Journal of Nutrition.
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.