Gen Iinuma

41 papers and 662 indexed citations i.

About

Gen Iinuma is a scholar working on Oncology, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Gen Iinuma has authored 41 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Oncology, 18 papers in Surgery and 16 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Gen Iinuma’s work include Colorectal Cancer Screening and Detection (17 papers), Colorectal Cancer Surgical Treatments (12 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Gen Iinuma is often cited by papers focused on Colorectal Cancer Screening and Detection (17 papers), Colorectal Cancer Surgical Treatments (12 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Gen Iinuma collaborates with scholars based in Japan, United States and United Kingdom. Gen Iinuma's co-authors include Takayuki Akasu, Noriyuki Moriyama, Yukio Muramatsu, Yutaka Saito, Hiroyuki Tsuda, Daizo Saito, Yasuo Ohashi, Tadao Kakizoe, Takahiro Kozu and Masaaki Iigo and has published in prestigious journals such as Journal of Clinical Oncology, Radiology and International Journal of Molecular Sciences.

In The Last Decade

Co-authorship network of co-authors of Gen Iinuma i

Fields of papers citing papers by Gen Iinuma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Gen Iinuma

Since Specialization
Citations

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