Awais Mansoor
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine top 10%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Artificial Intelligence
- Co-authors
- Ulaş BağcıDaniel J. MolluraZiyue XuBrent FosterJayaram K. UdupaGeorgios Z. PapadakisLes FolioKenneth N. Olivier
- Topics
- Radiomics and Machine Learning in Medical Imaging (4 papers)Lung Cancer Diagnosis and Treatment (4 papers)COVID-19 diagnosis using AI (4 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionPulmonary and Respiratory Medicine
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Awais Mansoor
10 papers receiving 611 citations
Peers
Comparison fields: 5 of 89
- Radiology, Nuclear Medicine and Imaging 468
- Pulmonary and Respiratory Medicine 226
- Computer Vision and Pattern Recognition 175
- Biomedical Engineering 116
- Artificial Intelligence 91
Countries citing papers authored by Awais Mansoor
This map shows the geographic impact of Awais Mansoor'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 Awais Mansoor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Awais Mansoor more than expected).
Fields of papers citing papers by Awais Mansoor
This network shows the impact of papers produced by Awais Mansoor. 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 Awais Mansoor. The network helps show where Awais Mansoor may publish in the future.
Co-authorship network of co-authors of Awais Mansoor
This figure shows the co-authorship network connecting the top 25 collaborators of Awais Mansoor. A scholar is included among the top collaborators of Awais Mansoor 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 Awais Mansoor. Awais Mansoor is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 30 | |
| 3 | 12 | |
| 4 | 170 | |
| 5 | 259 | |
| 6 | 118 | |
| 7 | 14 | |
| 8 | 12 | |
| 9 | Accurate quantification of brown adipose tissue through PET-guided CT image segmentation | 2 |
| 10 | 11 |
About Awais Mansoor
Awais Mansoor is a scholar working on Radiology, Nuclear Medicine and Imaging, Periodontics and Biophysics, having authored 10 papers that have together received 629 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Lung Cancer Diagnosis and Treatment (4 papers) and COVID-19 diagnosis using AI (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (468 citations), Computer Vision and Pattern Recognition (175 citations) and Pulmonary and Respiratory Medicine (226 citations). Awais Mansoor has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Ulaş Bağcı, Daniel J. Mollura, Ziyue Xu, Brent Foster, Jayaram K. Udupa, Georgios Z. Papadakis, Les Folio, Kenneth N. Olivier, Jason M. Elinoff and Anthony F. Suffredini. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Physics and Radiographics.
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.