Rosa Sicilia

About

Rosa Sicilia is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Rosa Sicilia has authored 19 papers receiving a total of 232 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 10 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Rosa Sicilia’s work include Radiomics and Machine Learning in Medical Imaging (8 papers), AI in cancer detection (6 papers) and Complex Network Analysis Techniques (4 papers). Rosa Sicilia is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (8 papers), AI in cancer detection (6 papers) and Complex Network Analysis Techniques (4 papers). Rosa Sicilia collaborates with scholars based in Italy, Sweden and The Netherlands. Rosa Sicilia's co-authors include Paolo Soda, Ermanno Cordelli, Mykola Pechenizkiy, Yulong Pei, Giulio Iannello, Sara Ramella, Edy Ippolito, Valerio Guarrasi, Mario Merone and Michele Fiore and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.

In The Last Decade

Co-authorship network of co-authors of Rosa Sicilia i

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Fields of papers citing papers by Rosa Sicilia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Rosa Sicilia

Since Specialization

Citations

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