Pranjal Vaidya
- Radiology, Nuclear Medicine and Imaging top 10%
- Pulmonary and Respiratory Medicine
- Oncology
- Artificial Intelligence
- Biomedical Engineering
- Co-authors
- Anant MadabhushiKaustav BeraVamsidhar VelchetiPradnya D. PatilAmit GuptaMehdi AlilouMohammadhadi KhorramiHumberto Choi
- Topics
- Radiomics and Machine Learning in Medical Imaging (13 papers)Lung Cancer Diagnosis and Treatment (8 papers)Advanced X-ray and CT Imaging (4 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingHealth InformaticsPulmonary and Respiratory Medicine
- Journals
- Journal of Clinical OncologySHILAP Revista de lepidopterologíaJournal of Thoracic Oncology
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Pranjal Vaidya
15 papers receiving 276 citations
Peers
Comparison fields: 5 of 35
- Radiology, Nuclear Medicine and Imaging 223
- Pulmonary and Respiratory Medicine 140
- Oncology 97
- Artificial Intelligence 54
- Biomedical Engineering 53
Countries citing papers authored by Pranjal Vaidya
This map shows the geographic impact of Pranjal Vaidya'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 Pranjal Vaidya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pranjal Vaidya more than expected).
Fields of papers citing papers by Pranjal Vaidya
This network shows the impact of papers produced by Pranjal Vaidya. 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 Pranjal Vaidya. The network helps show where Pranjal Vaidya may publish in the future.
Co-authorship network of co-authors of Pranjal Vaidya
This figure shows the co-authorship network connecting the top 25 collaborators of Pranjal Vaidya. A scholar is included among the top collaborators of Pranjal Vaidya 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 Pranjal Vaidya. Pranjal Vaidya 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 | 0 | |
| 3 | 5 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 15 | |
| 7 | 8 | |
| 8 | 34 | |
| 9 | 96 | |
| 10 | 80 | |
| 11 | 1 | |
| 12 | 9 | |
| 13 | 2 | |
| 14 | 13 | |
| 15 | 5 | |
| 16 | 2 |
About Pranjal Vaidya
Pranjal Vaidya is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Hepatology, having authored 16 papers that have together received 277 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (13 papers), Lung Cancer Diagnosis and Treatment (8 papers) and Advanced X-ray and CT Imaging (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (223 citations), Health Informatics (9 citations) and Pulmonary and Respiratory Medicine (140 citations). Pranjal Vaidya has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Anant Madabhushi, Kaustav Bera, Vamsidhar Velcheti, Pradnya D. Patil, Amit Gupta, Mehdi Alilou, Mohammadhadi Khorrami, Humberto Choi, Pingfu Fu and Prantesh Jain. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Journal of Thoracic 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.