Sandeep R. Bhave
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging top 10%
- Oncology
- Cancer Research
- Cell Biology
- Co-authors
- Dennis E. HallahanJerry J. JaboinDinesh ThotalaD.J. FerraroLori R. ArlinghausThomas E. YankeelovA. Bapsi ChakravarthyVandana G. Abramson
- Topics
- Radiomics and Machine Learning in Medical Imaging (6 papers)Cancer Immunotherapy and Biomarkers (4 papers)Sarcoma Diagnosis and Treatment (2 papers)
- Journals
- PLoS ONEInternational Journal of Radiation Oncology*Biology*PhysicsMagnetic Resonance in Medicine
- Partner nations
- United States
In The Last Decade
Sandeep R. Bhave
11 papers receiving 450 citations
Peers
Comparison fields: 5 of 82
- Molecular Biology 209
- Radiology, Nuclear Medicine and Imaging 161
- Oncology 68
- Cancer Research 66
- Cell Biology 42
Countries citing papers authored by Sandeep R. Bhave
This map shows the geographic impact of Sandeep R. Bhave'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 Sandeep R. Bhave with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandeep R. Bhave more than expected).
Fields of papers citing papers by Sandeep R. Bhave
This network shows the impact of papers produced by Sandeep R. Bhave. 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 Sandeep R. Bhave. The network helps show where Sandeep R. Bhave may publish in the future.
Co-authorship network of co-authors of Sandeep R. Bhave
This figure shows the co-authorship network connecting the top 25 collaborators of Sandeep R. Bhave. A scholar is included among the top collaborators of Sandeep R. Bhave 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 Sandeep R. Bhave. Sandeep R. Bhave is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 5 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 40 | |
| 6 | 20 | |
| 7 | 47 | |
| 8 | 97 | |
| 9 | 197 | |
| 10 | 6 | |
| 11 | Early prediction of the response of breast tumors to neoadjuvant chemotherapy using quantitative MRI and machine learning. | 21 |
About Sandeep R. Bhave
Sandeep R. Bhave is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Information Management and Oncology, having authored 11 papers that have together received 455 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Cancer Immunotherapy and Biomarkers (4 papers) and Sarcoma Diagnosis and Treatment (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (161 citations), Cancer Research (66 citations) and Molecular Biology (209 citations). Sandeep R. Bhave has collaborated with scholars based in United States. Frequent co-authors include Dennis E. Hallahan, Jerry J. Jaboin, Dinesh Thotala, D.J. Ferraro, Lori R. Arlinghaus, Thomas E. Yankeelov, A. Bapsi Chakravarthy, Vandana G. Abramson, Xia Li and Mark C. Kelley. Their work appears in journals such as PLoS ONE, International Journal of Radiation Oncology*Biology*Physics and Magnetic Resonance in Medicine.
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.