Mudalsha Ravina
- Surgery
- Infectious Diseases
- Pulmonary and Respiratory Medicine
- Radiology, Nuclear Medicine and Imaging
- Epidemiology
- Co-authors
- Sanjay GambhirManish DixitSukanta BaraiJamshed BomanjiSøren HessAbass AlaviSina HoushmandAli Salavati
- Topics
- Radiomics and Machine Learning in Medical Imaging (7 papers)Medical Imaging Techniques and Applications (4 papers)Medical Imaging and Pathology Studies (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the Neurological SciencesBritish Journal of Radiology
- Partner nations
- IndiaDenmarkUnited States
In The Last Decade
Mudalsha Ravina
31 papers receiving 258 citations
Peers
Comparison fields: 5 of 50
- Surgery 124
- Infectious Diseases 76
- Pulmonary and Respiratory Medicine 70
- Radiology, Nuclear Medicine and Imaging 45
- Epidemiology 38
Countries citing papers authored by Mudalsha Ravina
This map shows the geographic impact of Mudalsha Ravina'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 Mudalsha Ravina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mudalsha Ravina more than expected).
Fields of papers citing papers by Mudalsha Ravina
This network shows the impact of papers produced by Mudalsha Ravina. 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 Mudalsha Ravina. The network helps show where Mudalsha Ravina may publish in the future.
Co-authorship network of co-authors of Mudalsha Ravina
This figure shows the co-authorship network connecting the top 25 collaborators of Mudalsha Ravina. A scholar is included among the top collaborators of Mudalsha Ravina 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 Mudalsha Ravina. Mudalsha Ravina 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 7 | |
| 13 | 83 | |
| 14 | 18 | |
| 15 | 18 | |
| 16 | 14 | |
| 17 | 9 | |
| 18 | 4 | |
| 19 | 7 | |
| 20 | 2 |
About Mudalsha Ravina
Mudalsha Ravina is a scholar working on Internal Medicine, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 36 papers that have together received 261 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), Medical Imaging Techniques and Applications (4 papers) and Medical Imaging and Pathology Studies (4 papers). The work is most often cited by research in Internal Medicine (24 citations), Infectious Diseases (76 citations) and Nephrology (26 citations). Mudalsha Ravina has collaborated with scholars based in India, Denmark and United States. Frequent co-authors include Sanjay Gambhir, Manish Dixit, Sukanta Barai, Jamshed Bomanji, Søren Hess, Abass Alavi, Sina Houshmand, Ali Salavati, Mritunjai Kumar and Sanjeev Kumar Bhoi. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the Neurological Sciences and British Journal of 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.