Ajit Rajasekharan

2 papers and 142 indexed citations i.

About

Ajit Rajasekharan is a scholar working on Artificial Intelligence, Health Informatics and Industrial relations. According to data from OpenAlex, Ajit Rajasekharan has authored 2 papers receiving a total of 142 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Health Informatics and 0 papers in Industrial relations. Recurrent topics in Ajit Rajasekharan’s work include Machine Learning in Healthcare (2 papers), Topic Modeling (2 papers) and Natural Language Processing Techniques (1 paper). Ajit Rajasekharan is often cited by papers focused on Machine Learning in Healthcare (2 papers), Topic Modeling (2 papers) and Natural Language Processing Techniques (1 paper). Ajit Rajasekharan collaborates with scholars based in India and United States. Ajit Rajasekharan's co-authors include S. Sangeetha, Katikapalli Subramanyam Kalyan, Bradley Malin, William A. Faubion, J. Anderson, Vineet Agarwal, Sairam Bade, Jason Ross, John Halamka and Venky Soundararajan and has published in prestigious journals such as Journal of Biomedical Informatics and Patterns.

In The Last Decade

Co-authorship network of co-authors of Ajit Rajasekharan i

Fields of papers citing papers by Ajit Rajasekharan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ajit Rajasekharan. 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 Ajit Rajasekharan. The network helps show where Ajit Rajasekharan may publish in the future.

Countries citing papers authored by Ajit Rajasekharan

Since Specialization
Citations

This map shows the geographic impact of Ajit Rajasekharan'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 Ajit Rajasekharan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ajit Rajasekharan 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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