Suyash Mohan
- Health Informatics top 0.5%
- Genetics top 1%
- Glioma Diagnosis and Treatment 49
-
- Radiomics and Machine Learning in Medical Imaging 31
- MRI in cancer diagnosis 23
- Advanced Neuroimaging Techniques and Applications 13
- Medical Imaging Techniques and Applications 11
- Advanced MRI Techniques and Applications 11
- Radiology practices and education 11
- Neurology top 2%
- Vascular Malformations Diagnosis and Treatment 10
- Neurology top 5%
- Vascular Malformations Diagnosis and Treatment 10
- Co-authors
- Andreas M. RauscheckerJeffrey D. RudieC. C. Tchoyoson LimAmogh N. HegdeR. Nick BryanNarayan LathSanjeev ChawlaChristos Davatzikos
- Journals
- American Journal of Neuroradiology (15 papers)Academic Radiology (6 papers)Neuro-Oncology (6 papers)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Suyash Mohan
144 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 134
- Health Informatics 185
- Genetics 734
- Radiology, Nuclear Medicine and Imaging 1.2k
- Neurology 517
- Neurology 231
Countries citing papers authored by Suyash Mohan
This map shows the geographic impact of Suyash Mohan'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 Suyash Mohan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suyash Mohan more than expected).
Fields of papers citing papers by Suyash Mohan
This network shows the impact of papers produced by Suyash Mohan. 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 Suyash Mohan. The network helps show where Suyash Mohan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Suyash Mohan, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 3 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 6 | |
| 8 | 2023 | 12 | |
| 9 | 2023 | 19 | |
| 10 | 2023 | 15 | |
| 11 | 2022 | 2 | |
| 12 | 2022 | 23 | |
| 13 | 2021 | 3 | |
| 14 | 2020 | 4 | |
| 15 | 2020 | 18 | |
| 16 | 2019 | 18 | |
| 17 | 2019 | 56 | |
| 18 | 2017 | 1 | |
| 19 | 2017 | 22 | |
| 20 | 2017 | 37 |
About Suyash Mohan
Suyash Mohan is a scholar working on Genetics, Health Informatics, Radiology, Nuclear Medicine and Imaging, Structural Biology and Otorhinolaryngology, having authored 153 papers that have together received 2.8k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (49 papers), Radiomics and Machine Learning in Medical Imaging (31 papers), MRI in cancer diagnosis (23 papers), Advanced Neuroimaging Techniques and Applications (13 papers), Medical Imaging Techniques and Applications (11 papers), Advanced MRI Techniques and Applications (11 papers), Radiology practices and education (11 papers) and Vascular Malformations Diagnosis and Treatment (10 papers). The work is most often cited by research in Health Informatics (185 citations), Genetics (734 citations), Radiology, Nuclear Medicine and Imaging (1.2k citations), Neurology (517 citations) and Neurology (231 citations). Suyash Mohan has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Andreas M. Rauschecker, Jeffrey D. Rudie, C. C. Tchoyoson Lim, Amogh N. Hegde, R. Nick Bryan, Narayan Lath, Sanjeev Chawla, Christos Davatzikos, Michael Tran Duong and Harish Poptani. Their work appears in journals such as American Journal of Neuroradiology, Academic Radiology, Neuro-Oncology, Neuroimaging Clinics of North America and Clinical Radiology.
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.