Sharon Jiang
Impact in
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- Artificial Intelligence in Healthcare and Education
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- Pharmacogenetics and Drug Metabolism
Papers in
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- Frailty in Older Adults 2
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- Advanced Causal Inference Techniques 2
- Co-authors
- Kenney Ng (2 shared papers)Stan N. Finkelstein (2 shared papers)Roy E. Welsch (2 shared papers)Raymond H. Mak (2 shared papers)Adil Hussain Haider (1 shared paper)Dorothee Foernzler (1 shared paper)Arya S Rao (1 shared paper)Nicholas Kurtzman (1 shared paper)
- Journals
- Journal of the American Medical Informatics Association (2 papers)JAMA Network Open (1 paper)International Journal of Radiation Oncology*Biology*Physics (1 paper)Journal of the American College of Surgeons (1 paper)Journal of Geriatric Oncology (1 paper)
- Partner nations
- United StatesNetherlandsSwitzerland
In The Last Decade
Sharon Jiang
6 papers receiving 16 citations
Peers
Comparison fields: 5 of 6
- Health Informatics 3
- Pharmacology 3
- Statistics and Probability 3
- Genetics 2
- Artificial Intelligence 2
Countries citing papers authored by Sharon Jiang
This map shows the geographic impact of Sharon Jiang'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 Sharon Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sharon Jiang more than expected).
Fields of papers citing papers by Sharon Jiang
This network shows the impact of papers produced by Sharon Jiang. 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 Sharon Jiang. The network helps show where Sharon Jiang may publish in the future.
Co-authors
The 25 scholars most cited alongside Sharon Jiang, 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 | 2007 | 5 | |
| 2 | 2022 | 5 | |
| 3 | 2026 | 3 | |
| 4 | State of the Art Causal Inference in the Presence of Extraneous Covariates: A Simulation Study. | 2021 | 1 |
| 5 | 2024 | 1 | |
| 6 | 2025 | 1 | |
| 7 | 2025 | 0 | |
| 8 | 2025 | 0 | |
| 9 | 2026 | 0 |
About Sharon Jiang
Sharon Jiang is a scholar working on Geriatrics and Gerontology, Statistics and Probability, Health Informatics, Public Health, Environmental and Occupational Health and Artificial Intelligence, having authored 9 papers that have together received 16 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (2 papers), Frailty in Older Adults (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Innovations in Medical Education (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Health Informatics (3 citations), Pharmacology (3 citations), Statistics and Probability (3 citations), Genetics (2 citations) and Artificial Intelligence (2 citations). Sharon Jiang has collaborated with scholars based in United States, Netherlands and Switzerland. Frequent co-authors include Kenney Ng, Stan N. Finkelstein, Roy E. Welsch, Raymond H. Mak, Adil Hussain Haider, Dorothee Foernzler, Arya S Rao, Nicholas Kurtzman, Gezzer Ortega and Marc D. Succi. Their work appears in journals such as Journal of the American Medical Informatics Association, JAMA Network Open, International Journal of Radiation Oncology*Biology*Physics, Journal of the American College of Surgeons and Journal of Geriatric Oncology.
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.