Carol E. Reiley
Impact in
- Surgery top 5%
- Surgical Simulation and Training
-
- Augmented Reality Applications
Papers in
- Surgery 6
- Surgical Simulation and Training 6
-
- Augmented Reality Applications 5
- Co-authors
- Gregory D. Hager (6 shared papers)David D. Yuh (5 shared papers)Henry Lin (3 shared papers)Balázs Vágvölgyi (2 shared papers)Darius Burschka (3 shared papers)Takintope Akinbiyi (3 shared papers)Allison M. Okamura (3 shared papers)Rahul Agarwal (1 shared paper)
- Journals
- Journal of Thoracic and Cardiovascular Surgery (1 paper)Urology (1 paper)Surgical Endoscopy (1 paper)Lecture notes in computer science (2 papers)Journal of Robotic Surgery (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Carol E. Reiley
10 papers receiving 863 citations
Peers
Comparison fields: 5 of 64
- Surgery 516
- Computer Vision and Pattern Recognition 258
- Human-Computer Interaction 64
- Biomedical Engineering 381
- Health Informatics 7
Countries citing papers authored by Carol E. Reiley
This map shows the geographic impact of Carol E. Reiley'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 Carol E. Reiley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carol E. Reiley more than expected).
Fields of papers citing papers by Carol E. Reiley
This network shows the impact of papers produced by Carol E. Reiley. 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 Carol E. Reiley. The network helps show where Carol E. Reiley may publish in the future.
Co-authors
The 17 scholars most cited alongside Carol E. Reiley, 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 | 2010 | 190 | |
| 2 | 2009 | 176 | |
| 3 | 2008 | 164 | |
| 4 | 2009 | 107 | |
| 5 | 2010 | 69 | |
| 6 | 2009 | 69 | |
| 7 | Automatic recognition of surgical motions using statistical modeling for capturing variability. | 2008 | 58 |
| 8 | 2006 | 47 | |
| 9 | 2013 | 5 | |
| 10 | 2006 | 3 |
About Carol E. Reiley
Carol E. Reiley is a scholar working on Surgery, Computer Vision and Pattern Recognition, Biomedical Engineering, Signal Processing and Computational Mechanics, having authored 10 papers that have together received 888 indexed citations. Recurring topics across this work include Surgical Simulation and Training (6 papers), Augmented Reality Applications (5 papers), Anatomy and Medical Technology (3 papers), Machine Learning and Algorithms (1 paper), AI-based Problem Solving and Planning (1 paper), Soft Robotics and Applications (1 paper), Time Series Analysis and Forecasting (1 paper) and 3D Shape Modeling and Analysis (1 paper). The work is most often cited by research in Surgery (516 citations), Computer Vision and Pattern Recognition (258 citations), Human-Computer Interaction (64 citations), Biomedical Engineering (381 citations) and Health Informatics (7 citations). Carol E. Reiley has collaborated with scholars based in United States and Germany. Frequent co-authors include Gregory D. Hager, David D. Yuh, Henry Lin, Balázs Vágvölgyi, Darius Burschka, Takintope Akinbiyi, Allison M. Okamura, Rahul Agarwal, Russell H. Taylor and Li-Ming Su. Their work appears in journals such as Journal of Thoracic and Cardiovascular Surgery, Urology, Surgical Endoscopy, Lecture notes in computer science and Journal of Robotic Surgery.
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.