Shivam Kalra
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Health Informatics top 5%
- Oncology
- Co-authors
- Hamid R. TizhooshJesse C. CresswellGraham W. TaylorMohammed AdnanClinton J.V. CampbellPhedias DiamandisMaksims VolkovsLiron Pantanowitz
- Topics
- AI in cancer detection (10 papers)Image Retrieval and Classification Techniques (4 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)
- Partner nations
- CanadaUnited StatesIndia
In The Last Decade
Shivam Kalra
17 papers receiving 443 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 341
- Radiology, Nuclear Medicine and Imaging 137
- Computer Vision and Pattern Recognition 96
- Health Informatics 49
- Oncology 37
Countries citing papers authored by Shivam Kalra
This map shows the geographic impact of Shivam Kalra'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 Shivam Kalra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shivam Kalra more than expected).
Fields of papers citing papers by Shivam Kalra
This network shows the impact of papers produced by Shivam Kalra. 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 Shivam Kalra. The network helps show where Shivam Kalra may publish in the future.
Co-authorship network of co-authors of Shivam Kalra
This figure shows the co-authorship network connecting the top 25 collaborators of Shivam Kalra. A scholar is included among the top collaborators of Shivam Kalra 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 Shivam Kalra. Shivam Kalra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Decentralized federated learning through proxy model sharingbreakdown → | 73 |
| 3 | 6 | |
| 4 | 11 | |
| 5 | Federated learning and differential privacy for medical image analysisbreakdown → | 191 |
| 6 | 12 | |
| 7 | 34 | |
| 8 | CNN and Deep Sets for End-to-End Whole Slide Image Representation Learning | 4 |
| 9 | 4 | |
| 10 | 76 | |
| 11 | 7 | |
| 12 | 3 | |
| 13 | 3 | |
| 14 | 8 | |
| 15 | 12 | |
| 16 | 3 | |
| 17 | 4 |
About Shivam Kalra
Shivam Kalra is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 17 papers that have together received 453 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Image Retrieval and Classification Techniques (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Health Informatics (49 citations), Artificial Intelligence (341 citations) and Radiology, Nuclear Medicine and Imaging (137 citations). Shivam Kalra has collaborated with scholars based in Canada, United States and India. Frequent co-authors include Hamid R. Tizhoosh, Jesse C. Cresswell, Graham W. Taylor, Mohammed Adnan, Clinton J.V. Campbell, Phedias Diamandis, Maksims Volkovs, Liron Pantanowitz, Charles Q. Choi and Sultaan Shah. Their work appears in journals such as Nature Communications, Scientific Reports and American Journal Of Pathology.
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.