Sarah Hickman

17 papers and 386 indexed citations i.

About

Sarah Hickman is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Sarah Hickman has authored 17 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Sarah Hickman’s work include AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Sarah Hickman is often cited by papers focused on AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Sarah Hickman collaborates with scholars based in United Kingdom, Australia and United States. Sarah Hickman's co-authors include Fiona J. Gilbert, Elizabeth Le, Yuan Huang, Yanzhong Wang, Gabrielle Baxter, Yu Ri Im, James Mackay, Ramona Woitek, Angelica I. Avilés-Rivero and Marije van Melle and has published in prestigious journals such as Radiology, Free Radical Biology and Medicine and British Journal of Cancer.

In The Last Decade

Co-authorship network of co-authors of Sarah Hickman i

Fields of papers citing papers by Sarah Hickman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Sarah Hickman

Since Specialization
Citations

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