Radiomics: Extracting more information from medical images using advanced feature analysis

Abstract

loading...

About

This paper, published in 1950, received 4.1k indexed citations. Written by Philippe Lambin, Ralph T. H. Leijenaar, Sara Carvalho, Ruud G.P.M. van Stiphout, Patrick V. Granton, Catharina M.L. Zegers, Robert J. Gillies, Ronald Boellard, André Dekker and Hugo J.W.L. Aerts covering the research area of Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. It is primarily cited by scholars working on Radiology, Nuclear Medicine and Imaging (3.7k citations), Pulmonary and Respiratory Medicine (1.4k citations) and Biomedical Engineering (976 citations). Published in European Journal of Cancer.

Countries where authors are citing Radiomics: Extracting more information from medical images using advanced feature analysis

Since Specialization
Citations

This map shows the geographic impact of Radiomics: Extracting more information from medical images using advanced feature analysis. 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 Radiomics: Extracting more information from medical images using advanced feature analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Radiomics: Extracting more information from medical images using advanced feature analysis more than expected).

Fields of papers citing Radiomics: Extracting more information from medical images using advanced feature analysis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Radiomics: Extracting more information from medical images using advanced feature analysis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Radiomics: Extracting more information from medical images using advanced feature analysis.

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.

This paper is also available at doi.org/10.1016/j.ejca.2011.11.036.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026