Amber Donnelly

34 papers and 369 indexed citations i.

About

Amber Donnelly is a scholar working on Epidemiology, Oncology and Artificial Intelligence. According to data from OpenAlex, Amber Donnelly has authored 34 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Epidemiology, 8 papers in Oncology and 7 papers in Artificial Intelligence. Recurrent topics in Amber Donnelly’s work include Cervical Cancer and HPV Research (10 papers), AI in cancer detection (7 papers) and Radiology practices and education (4 papers). Amber Donnelly is often cited by papers focused on Cervical Cancer and HPV Research (10 papers), AI in cancer detection (7 papers) and Radiology practices and education (4 papers). Amber Donnelly collaborates with scholars based in United States, South Africa and Portugal. Amber Donnelly's co-authors include Maheswari Mukherjee, Stanley J. Radio, Elizabeth Lyden, Stephen S. Raab, Eric J. Suba, R. Marshall Austin, Timothy Leaven, Sue Zaleski, Mathilde E. Boon and Clarence D. Kreiter and has published in prestigious journals such as Journal of the American Chemical Society, Cancer and American Journal of Public Health.

In The Last Decade

Co-authorship network of co-authors of Amber Donnelly i

Fields of papers citing papers by Amber Donnelly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Amber Donnelly

Since Specialization
Citations

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