Sunit Das
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Internal Medicine top 0.5%
- Venous Thromboembolism Diagnosis and Management
Papers in ⓘ
- Genetics 79
- Glioma Diagnosis and Treatment 78
- Co-authors
- Arjun Sahgal (57 shared papers)Philip A. Marsden (2 shared papers)Jason Karamchandani (8 shared papers)John A. Kessler (8 shared papers)Hany Soliman (28 shared papers)A.T. Cohen (4 shared papers)D. James Cooper (4 shared papers)Maya Srikanth (4 shared papers)
- Journals
- Journal of Neuro-Oncology (17 papers)International Journal of Radiation Oncology*Biology*Physics (10 papers)Neuro-Oncology (8 papers)Neuro-Oncology Advances (8 papers)Frontiers in Oncology (8 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Sunit Das
183 papers receiving 4.4k citations
Peers
Comparison fields: 5 of 152
- Health Informatics 200
- Internal Medicine 554
- Genetics 1.2k
- Cancer Research 591
- Developmental Neuroscience 145
Countries citing papers authored by Sunit Das
This map shows the geographic impact of Sunit Das'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 Sunit Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunit Das more than expected).
Fields of papers citing papers by Sunit Das
This network shows the impact of papers produced by Sunit Das. 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 Sunit Das. The network helps show where Sunit Das may publish in the future.
Co-authors
The 25 scholars most cited alongside Sunit Das, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 193 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1993 | 217 | |
| 2 | 2013 | 210 | |
| 3 | 1993 | 209 | |
| 4 | 2004 | 168 | |
| 5 | 2014 | 158 | |
| 6 | 2020 | 142 | |
| 7 | 2020 | 133 | |
| 8 | 1996 | 124 | |
| 9 | 2018 | 118 | |
| 10 | 2016 | 106 | |
| 11 | 2008 | 100 | |
| 12 | 2009 | 96 | |
| 13 | 2021 | 89 | |
| 14 | 2017 | 83 | |
| 15 | 2015 | 77 | |
| 16 | 2021 | 73 | |
| 17 | 2018 | 73 | |
| 18 | 2003 | 64 | |
| 19 | 2019 | 63 | |
| 20 | 1994 | 62 |
About Sunit Das
Sunit Das is a scholar working on Genetics, Health Informatics, Pulmonary and Respiratory Medicine, Oncology and Developmental Neuroscience, having authored 193 papers that have together received 4.5k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (78 papers), Brain Metastases and Treatment (51 papers), Meningioma and schwannoma management (26 papers), Lung Cancer Research Studies (24 papers), Advanced MRI Techniques and Applications (11 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Cancer Cells and Metastasis (10 papers) and Neuroblastoma Research and Treatments (6 papers). The work is most often cited by research in Health Informatics (200 citations), Internal Medicine (554 citations), Genetics (1.2k citations), Cancer Research (591 citations) and Developmental Neuroscience (145 citations). Sunit Das has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Arjun Sahgal, Philip A. Marsden, Jason Karamchandani, John A. Kessler, Hany Soliman, A.T. Cohen, D. James Cooper, Maya Srikanth, James Perry and Liam G. McCoy. Their work appears in journals such as Journal of Neuro-Oncology, International Journal of Radiation Oncology*Biology*Physics, Neuro-Oncology, Neuro-Oncology Advances and Frontiers in Oncology.
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.