Patricia Raciti

10 papers and 230 indexed citations i.

About

Patricia Raciti is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Patricia Raciti has authored 10 papers receiving a total of 230 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Patricia Raciti’s work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Prostate Cancer Diagnosis and Treatment (4 papers). Patricia Raciti is often cited by papers focused on AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Prostate Cancer Diagnosis and Treatment (4 papers). Patricia Raciti collaborates with scholars based in United States, United Kingdom and Italy. Patricia Raciti's co-authors include David S. Klimstra, Christopher Kanan, Jillian Sue, Jeremy D. Kunz, Victor E. Reuter, Ran Godrich, Leo Grady, Thomas J. Fuchs, Brandon Rothrock and Sudhir Perincheri and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Cancer Research.

In The Last Decade

Co-authorship network of co-authors of Patricia Raciti i

Fields of papers citing papers by Patricia Raciti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Patricia Raciti

Since Specialization
Citations

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