Frank Yoon
Impact in
- Statistics and Probability top 10%
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Oral Surgery top 10%
Papers in
-
- Advanced Causal Inference Techniques 4
- Statistical Methods and Bayesian Inference 3
- Statistical Methods and Inference 2
- Oncology 2
- Cutaneous Melanoma Detection and Management 2
- Co-authors
- Mian Iqbal (1 shared paper)Sara Kim (1 shared paper)Teresa B. Gibson (4 shared papers)Patrick T. O’Gara (2 shared papers)Bernard Prendergast (2 shared papers)Peter B. Lockhart (2 shared papers)Mark Dayer (2 shared papers)Larry M. Baddour (2 shared papers)
- Journals
- Journal of Clinical Oncology (2 papers)Statistics in Medicine (2 papers)Journal of the American Medical Informatics Association (1 paper)Journal of Endodontics (1 paper)Oral Diseases (1 paper)
- Partner nations
- United StatesUnited KingdomIsrael
In The Last Decade
Frank Yoon
14 papers receiving 326 citations
Peers
Comparison fields: 5 of 72
- Statistics and Probability 36
- Oral Surgery 24
- General Health Professions 79
- Epidemiology 80
- Periodontics 11
Countries citing papers authored by Frank Yoon
This map shows the geographic impact of Frank Yoon'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 Frank Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Yoon more than expected).
Fields of papers citing papers by Frank Yoon
This network shows the impact of papers produced by Frank Yoon. 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 Frank Yoon. The network helps show where Frank Yoon may publish in the future.
Co-authors
The 25 scholars most cited alongside Frank Yoon, 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 | 2016 | 83 | |
| 2 | 2022 | 58 | |
| 3 | 2007 | 36 | |
| 4 | 2013 | 30 | |
| 5 | 2015 | 27 | |
| 6 | 2016 | 20 | |
| 7 | 2023 | 17 | |
| 8 | 2011 | 16 | |
| 9 | 2021 | 14 | |
| 10 | 2009 | 14 | |
| 11 | 2011 | 5 | |
| 12 | 2021 | 4 | |
| 13 | 2008 | 4 | |
| 14 | New methods for the design and analysis of observational studies | 2009 | 3 |
| 15 | 2016 | 0 |
About Frank Yoon
Frank Yoon is a scholar working on Statistics and Probability, Oncology, Epidemiology, Infectious Diseases and Molecular Biology, having authored 15 papers that have together received 331 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (4 papers), Statistical Methods and Bayesian Inference (3 papers), Cutaneous Melanoma Detection and Management (2 papers), Infective Endocarditis Diagnosis and Management (2 papers), Statistical Methods and Inference (2 papers), Autopsy Techniques and Outcomes (1 paper), Streptococcal Infections and Treatments (1 paper) and Primary Care and Health Outcomes (1 paper). The work is most often cited by research in Statistics and Probability (36 citations), Oral Surgery (24 citations), General Health Professions (79 citations), Epidemiology (80 citations) and Periodontics (11 citations). Frank Yoon has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Mian Iqbal, Sara Kim, Teresa B. Gibson, Patrick T. O’Gara, Bernard Prendergast, Peter B. Lockhart, Mark Dayer, Larry M. Baddour, Samuel D. Pimentel and Luke Keele. Their work appears in journals such as Journal of Clinical Oncology, Statistics in Medicine, Journal of the American Medical Informatics Association, Journal of Endodontics and Oral Diseases.
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.