Saima Rathore
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Oncology
- Pulmonary and Respiratory Medicine
- Co-authors
- Muhammad Aksam IftikharMutawarra HussainAbdul JalilAhmad ChaddadAhmad AliTamim NiaziAsifullah KhanMichel Bilello
- Topics
- Radiomics and Machine Learning in Medical Imaging (10 papers)AI in cancer detection (9 papers)Image and Signal Denoising Methods (4 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Partner nations
- PakistanUnited StatesCanada
In The Last Decade
Saima Rathore
26 papers receiving 544 citations
Peers
Comparison fields: 5 of 83
- Radiology, Nuclear Medicine and Imaging 269
- Artificial Intelligence 247
- Computer Vision and Pattern Recognition 210
- Oncology 86
- Pulmonary and Respiratory Medicine 60
Countries citing papers authored by Saima Rathore
This map shows the geographic impact of Saima Rathore'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 Saima Rathore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saima Rathore more than expected).
Fields of papers citing papers by Saima Rathore
This network shows the impact of papers produced by Saima Rathore. 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 Saima Rathore. The network helps show where Saima Rathore may publish in the future.
Co-authorship network of co-authors of Saima Rathore
This figure shows the co-authorship network connecting the top 25 collaborators of Saima Rathore. A scholar is included among the top collaborators of Saima Rathore 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 Saima Rathore. Saima Rathore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 22 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 31 | |
| 6 | 26 | |
| 7 | 21 | |
| 8 | 49 | |
| 9 | 23 | |
| 10 | 4 | |
| 11 | 25 | |
| 12 | 9 | |
| 13 | 33 | |
| 14 | 36 | |
| 15 | 11 | |
| 16 | 66 | |
| 17 | 87 | |
| 18 | 17 | |
| 19 | 9 | |
| 20 | 3 |
About Saima Rathore
Saima Rathore is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Radiology, Nuclear Medicine and Imaging, having authored 27 papers that have together received 559 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (9 papers) and Image and Signal Denoising Methods (4 papers). The work is most often cited by research in Health Informatics (17 citations), Radiology, Nuclear Medicine and Imaging (269 citations) and Computer Vision and Pattern Recognition (210 citations). Saima Rathore has collaborated with scholars based in Pakistan, United States and Canada. Frequent co-authors include Muhammad Aksam Iftikhar, Mutawarra Hussain, Abdul Jalil, Ahmad Chaddad, Ahmad Ali, Tamim Niazi, Asifullah Khan, Michel Bilello, Christian Desrosiers and Mingli Zhang. Their work appears in journals such as IEEE Access, Neurocomputing and JAMA Neurology.
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.