Emily B. Tsai
- Surgery
- Radiology, Nuclear Medicine and Imaging top 10%
- Genetics top 10%
- Pulmonary and Respiratory Medicine
- Endocrinology, Diabetes and Metabolism top 10%
- Co-authors
- Nicole SherryKevan C. HeroldJerry P. PalmerCurtis P. LanglotzDan JurafskyYasuhide MiuraYuhao ZhangSylvia K. Plevritis
- Topics
- Lung Cancer Diagnosis and Treatment (7 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)Advanced X-ray and CT Imaging (4 papers)
- Cited by
- Health InformaticsEndocrinology, Diabetes and MetabolismRadiology, Nuclear Medicine and Imaging
- Partner nations
- United StatesAustraliaSingapore
In The Last Decade
Emily B. Tsai
16 papers receiving 537 citations
Peers
Comparison fields: 5 of 61
- Surgery 207
- Radiology, Nuclear Medicine and Imaging 184
- Genetics 178
- Pulmonary and Respiratory Medicine 167
- Endocrinology, Diabetes and Metabolism 160
Countries citing papers authored by Emily B. Tsai
This map shows the geographic impact of Emily B. Tsai'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 Emily B. Tsai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emily B. Tsai more than expected).
Fields of papers citing papers by Emily B. Tsai
This network shows the impact of papers produced by Emily B. Tsai. 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 Emily B. Tsai. The network helps show where Emily B. Tsai may publish in the future.
Co-authorship network of co-authors of Emily B. Tsai
This figure shows the co-authorship network connecting the top 25 collaborators of Emily B. Tsai. A scholar is included among the top collaborators of Emily B. Tsai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emily B. Tsai. Emily B. Tsai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 13 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 22 | |
| 6 | 72 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 20 | |
| 10 | 30 | |
| 11 | 9 | |
| 12 | 23 | |
| 13 | 68 | |
| 14 | 4 | |
| 15 | 64 | |
| 16 | 82 | |
| 17 | 132 |
About Emily B. Tsai
Emily B. Tsai is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Internal Medicine, having authored 17 papers that have together received 548 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Advanced X-ray and CT Imaging (4 papers). The work is most often cited by research in Health Informatics (15 citations), Endocrinology, Diabetes and Metabolism (160 citations) and Radiology, Nuclear Medicine and Imaging (184 citations). Emily B. Tsai has collaborated with scholars based in United States, Australia and Singapore. Frequent co-authors include Nicole Sherry, Kevan C. Herold, Jerry P. Palmer, Curtis P. Langlotz, Dan Jurafsky, Yasuhide Miura, Yuhao Zhang, Sylvia K. Plevritis, Christoph I. Lee and Alan M. Garber. Their work appears in journals such as American Journal of Respiratory and Critical Care Medicine, Diabetes and Radiology.
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.