Prateek Mathur
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
-
- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- Soft Robotics and Applications 2
- Medical Imaging and Analysis 2
-
- Augmented Reality Applications 4
- Co-authors
- Septimiu E. Salcudean (6 shared papers)Brendan S. Kelly (4 shared papers)Ronan P. Killeen (4 shared papers)Aonghus Lawlor (5 shared papers)Conor Judge (1 shared paper)Gerard M. Healy (1 shared paper)Kristen W. Yeom (3 shared papers)S. Sara Mahdavi (1 shared paper)
- Journals
- International Journal of Computer Assisted Radiology and Surgery (3 papers)European Radiology (2 papers)Computers in Biology and Medicine (1 paper)European Journal of Radiology (1 paper)Medical Image Analysis (1 paper)
- Partner nations
- CanadaIrelandUnited States
In The Last Decade
Prateek Mathur
11 papers receiving 294 citations
Peers
Comparison fields: 5 of 72
- Health Informatics 82
- Radiology, Nuclear Medicine and Imaging 109
- Computer Vision and Pattern Recognition 66
- Family Practice 7
- Biomedical Engineering 115
Countries citing papers authored by Prateek Mathur
This map shows the geographic impact of Prateek Mathur'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 Prateek Mathur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prateek Mathur more than expected).
Fields of papers citing papers by Prateek Mathur
This network shows the impact of papers produced by Prateek Mathur. 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 Prateek Mathur. The network helps show where Prateek Mathur may publish in the future.
Co-authors
The 21 scholars most cited alongside Prateek Mathur, 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 | 2022 | 130 | |
| 2 | 2019 | 86 | |
| 3 | 2019 | 33 | |
| 4 | 2019 | 14 | |
| 5 | 2019 | 12 | |
| 6 | 2020 | 9 | |
| 7 | 2019 | 7 | |
| 8 | 2024 | 4 | |
| 9 | 2023 | 3 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 1 |
About Prateek Mathur
Prateek Mathur is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition, Surgery, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 11 papers that have together received 300 indexed citations. Recurring topics across this work include Augmented Reality Applications (4 papers), Surgical Simulation and Training (3 papers), Robotics and Sensor-Based Localization (2 papers), Soft Robotics and Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Prostate Cancer Diagnosis and Treatment (2 papers), Medical Imaging and Analysis (2 papers) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Informatics (82 citations), Radiology, Nuclear Medicine and Imaging (109 citations), Computer Vision and Pattern Recognition (66 citations), Family Practice (7 citations) and Biomedical Engineering (115 citations). Prateek Mathur has collaborated with scholars based in Canada, Ireland and United States. Frequent co-authors include Septimiu E. Salcudean, Brendan S. Kelly, Ronan P. Killeen, Aonghus Lawlor, Conor Judge, Gerard M. Healy, Kristen W. Yeom, S. Sara Mahdavi, Ingrid Spadinger and Davood Karimi. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, European Radiology, Computers in Biology and Medicine, European Journal of Radiology and Medical Image Analysis.
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.