Anna Maria Paganoni

93 papers and 1.3k indexed citations i.

About

Anna Maria Paganoni is a scholar working on Statistics and Probability, Artificial Intelligence and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Anna Maria Paganoni has authored 93 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Statistics and Probability, 17 papers in Artificial Intelligence and 11 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Anna Maria Paganoni’s work include Statistical Methods and Inference (21 papers), Advanced Statistical Methods and Models (14 papers) and Bayesian Methods and Mixture Models (9 papers). Anna Maria Paganoni is often cited by papers focused on Statistical Methods and Inference (21 papers), Advanced Statistical Methods and Models (14 papers) and Bayesian Methods and Mixture Models (9 papers). Anna Maria Paganoni collaborates with scholars based in Italy, United Kingdom and Spain. Anna Maria Paganoni's co-authors include Francesca Ieva, Piercesare Secchi, Alberto Barchielli, Chiara Masci, Laura M. Sangalli, Tommaso Agasisti, Simonetta Scalvini, Maria Pia Protti, Valeria Vitelli and Davide Pigoli and has published in prestigious journals such as Journal of Clinical Oncology, The Journal of Immunology and PLoS ONE.

In The Last Decade

Co-authorship network of co-authors of Anna Maria Paganoni i

Fields of papers citing papers by Anna Maria Paganoni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anna Maria Paganoni. 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 Anna Maria Paganoni. The network helps show where Anna Maria Paganoni may publish in the future.

Countries citing papers authored by Anna Maria Paganoni

Since Specialization
Citations

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