Intelligence-Based Medicine

226 papers and 1.4k indexed citations

About

The 226 papers published in Intelligence-Based Medicine in the last decades have received a total of 1.4k indexed citations. Papers published in Intelligence-Based Medicine usually cover Artificial Intelligence (75 papers), Radiology, Nuclear Medicine and Imaging (75 papers) and Health Informatics (29 papers) specifically the topics of COVID-19 diagnosis using AI (34 papers), AI in cancer detection (32 papers) and Machine Learning in Healthcare (31 papers). The most active scholars publishing in Intelligence-Based Medicine are Marcello Ienca, Felix Gille, Anna Jobin, Manas Ranjan Prusty, Anthony Chang, Anuj Pareek, Matthew P. Lungren, H. Russell Kunz, Anil Rawat and Candace Moore.

In The Last Decade

Intelligence-Based Medicine

171 papers receiving 1.3k citations

Countries where authors publish in Intelligence-Based Medicine

Since Specialization
Citations

This map shows the geographic impact of research published in Intelligence-Based Medicine. 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 papers published in Intelligence-Based Medicine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Intelligence-Based Medicine more than expected).

Fields of papers published in Intelligence-Based Medicine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Intelligence-Based Medicine. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Intelligence-Based Medicine.

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.

Explore journals with similar magnitude of impact

Rankless by CCL
2026