Emily Pellegrini

25 papers and 522 indexed citations i.

About

Emily Pellegrini is a scholar working on Artificial Intelligence, Epidemiology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Emily Pellegrini has authored 25 papers receiving a total of 522 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 9 papers in Epidemiology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Emily Pellegrini’s work include Sepsis Diagnosis and Treatment (9 papers), Machine Learning in Healthcare (8 papers) and COVID-19 diagnosis using AI (5 papers). Emily Pellegrini is often cited by papers focused on Sepsis Diagnosis and Treatment (9 papers), Machine Learning in Healthcare (8 papers) and COVID-19 diagnosis using AI (5 papers). Emily Pellegrini collaborates with scholars based in United States, China and Belgium. Emily Pellegrini's co-authors include Ritankar Das, Jana Hoffman, Jacob Calvert, Abigail Green‐Saxena, Sidney Le, Angier Allen, Hoyt Burdick, Andrea J. McCoy, Gina Barnes and Anna Siefkas and has published in prestigious journals such as Circulation, Critical Care Medicine and World Journal of Gastroenterology.

In The Last Decade

Co-authorship network of co-authors of Emily Pellegrini i

Fields of papers citing papers by Emily Pellegrini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Emily Pellegrini

Since Specialization
Citations

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