Subbaram Naidu
- Radiology, Nuclear Medicine and Imaging
- Artificial Intelligence
- Pulmonary and Respiratory Medicine
- Health Informatics top 10%
- Cardiology and Cardiovascular Medicine
- Co-authors
- Suneet Kumar GuptaAyman El‐BazZeno FalaschiLuca SabaAlessio PaschèAlessandro CarrieroPietro DannaJasjit S. Suri
- Topics
- COVID-19 diagnosis using AI (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)Artificial Intelligence in Healthcare and Education (2 papers)
- Journals
- IEEE Transactions on Instrumentation and MeasurementMultimedia Tools and ApplicationsSoft Computing
- Partner nations
- United StatesIndiaItaly
In The Last Decade
Subbaram Naidu
5 papers receiving 98 citations
Peers
Comparison fields: 5 of 42
- Radiology, Nuclear Medicine and Imaging 42
- Artificial Intelligence 30
- Pulmonary and Respiratory Medicine 24
- Health Informatics 22
- Cardiology and Cardiovascular Medicine 17
Countries citing papers authored by Subbaram Naidu
This map shows the geographic impact of Subbaram Naidu'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 Subbaram Naidu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subbaram Naidu more than expected).
Fields of papers citing papers by Subbaram Naidu
This network shows the impact of papers produced by Subbaram Naidu. 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 Subbaram Naidu. The network helps show where Subbaram Naidu may publish in the future.
Co-authorship network of co-authors of Subbaram Naidu
This figure shows the co-authorship network connecting the top 25 collaborators of Subbaram Naidu. A scholar is included among the top collaborators of Subbaram Naidu 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 Subbaram Naidu. Subbaram Naidu 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 | 2 | |
| 3 | 18 | |
| 4 | 15 | |
| 5 | 41 | |
| 6 | 24 |
About Subbaram Naidu
Subbaram Naidu is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Signal Processing, having authored 6 papers that have together received 100 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (22 citations), Radiology, Nuclear Medicine and Imaging (42 citations) and Health Information Management (6 citations). Subbaram Naidu has collaborated with scholars based in United States, India and Italy. Frequent co-authors include Suneet Kumar Gupta, Ayman El‐Baz, Zeno Falaschi, Luca Saba, Alessio Paschè, Alessandro Carriero, Luca Saba, Pietro Danna, Jasjit S. Suri and Mohit Agarwal. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Multimedia Tools and Applications and Soft Computing.
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.