George Shih
- Radiology, Nuclear Medicine and Imaging top 1%
- Health Informatics top 0.2%
- Artificial Intelligence top 5%
- Materials Chemistry
- Biomedical Engineering
- Co-authors
- Martin R. PrinceYan CaoLuciano M. PrevedelloSafwan S. HalabiMarc KohliAdam E. FlandersKatherine P. AndrioleBradley J. Erickson
- Topics
- Radiomics and Machine Learning in Medical Imaging (20 papers)COVID-19 diagnosis using AI (14 papers)Artificial Intelligence in Healthcare and Education (12 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
George Shih
65 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 124
- Radiology, Nuclear Medicine and Imaging 1000
- Health Informatics 347
- Artificial Intelligence 337
- Materials Chemistry 271
- Biomedical Engineering 204
Countries citing papers authored by George Shih
This map shows the geographic impact of George Shih'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 George Shih with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George Shih more than expected).
Fields of papers citing papers by George Shih
This network shows the impact of papers produced by George Shih. 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 George Shih. The network helps show where George Shih may publish in the future.
Co-authorship network of co-authors of George Shih
This figure shows the co-authorship network connecting the top 25 collaborators of George Shih. A scholar is included among the top collaborators of George Shih 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 George Shih. George Shih 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 | 6 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 5 | |
| 7 | 5 | |
| 8 | 36 | |
| 9 | 10 | |
| 10 | 181 | |
| 11 | 107 | |
| 12 | 283 | |
| 13 | 5 | |
| 14 | 4 | |
| 15 | Pitfalls and Sources of Error of Color Duplex Sonography in Screening for Renovascular Hypertension | 0 |
| 16 | 28 | |
| 17 | 31 | |
| 18 | 1 | |
| 19 | Illustrated Textbook of Pediatrics | 0 |
| 20 | Bodies of Evidence: Reconstructing History through Skeletal Analysis | 3 |
About George Shih
George Shih is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 70 papers that have together received 1.6k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (20 papers), COVID-19 diagnosis using AI (14 papers) and Artificial Intelligence in Healthcare and Education (12 papers). The work is most often cited by research in Health Informatics (347 citations), Radiology, Nuclear Medicine and Imaging (1000 citations) and Archeology (124 citations). George Shih has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Martin R. Prince, Yan Cao, Luciano M. Prevedello, Safwan S. Halabi, Marc Kohli, Adam E. Flanders, Katherine P. Andriole, Bradley J. Erickson, Jayashree Kalpathy–Cramer and Carol C. Wu. Their work appears in journals such as Nature Communications, Radiology and The Journal of Urology.
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.