Subbaram Naidu

5 papers and 78 indexed citations i.

About

Subbaram Naidu is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Health Informatics. According to data from OpenAlex, Subbaram Naidu has authored 5 papers receiving a total of 78 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Radiology, Nuclear Medicine and Imaging, 2 papers in Artificial Intelligence and 2 papers in Health Informatics. Recurrent topics in Subbaram Naidu’s work include COVID-19 diagnosis using AI (3 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Subbaram Naidu is often cited by papers focused on COVID-19 diagnosis using AI (3 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Subbaram Naidu collaborates with scholars based in Italy, India and United States. Subbaram Naidu's co-authors include Ayman El–Baz, Suneet Kumar Gupta, Alessio Paschè, Mohit Agarwal, Vikas Agarwal, Luca Saba, Luca Saba, Jasjit S. Suri, Jasjit S. Suri and Zeno Falaschi and has published in prestigious journals such as IEEE Transactions on Instrumentation and Measurement, Journal of Medical Systems and Multimedia Tools and Applications.

In The Last Decade

Co-authorship network of co-authors of Subbaram Naidu i

Fields of papers citing papers by Subbaram Naidu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Countries citing papers authored by Subbaram Naidu

Since Specialization
Citations

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).

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.

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2025