Jun‐ichiro Kuroda

63 total papers · 822 total citations
33 papers, 618 citations indexed

About

Jun‐ichiro Kuroda is a scholar working on Genetics, Neurology and Molecular Biology. According to data from OpenAlex, Jun‐ichiro Kuroda has authored 33 papers receiving a total of 618 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Genetics, 8 papers in Neurology and 7 papers in Molecular Biology. Recurrent topics in Jun‐ichiro Kuroda's work include Glioma Diagnosis and Treatment (17 papers), CNS Lymphoma Diagnosis and Treatment (4 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Jun‐ichiro Kuroda is often cited by papers focused on Glioma Diagnosis and Treatment (17 papers), CNS Lymphoma Diagnosis and Treatment (4 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Jun‐ichiro Kuroda collaborates with scholars based in Japan and United States. Jun‐ichiro Kuroda's co-authors include Masahiro Yasunaga, Yoshikatsu Koga, Yasuhiro Matsumura, Amane Takahashi, Jun‐ichi Kuratsu, Yoshihiro Moriya, Takayuki Akasu, Hideo A. Baba, Seiichiro Yamamoto and Shin Fujita and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Cancer.

In The Last Decade

Jun‐ichiro Kuroda

28 papers receiving 609 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jun‐ichiro Kuroda 272 175 166 138 127 33 618
Hyang‐Hwa Ryu 276 1.0× 84 0.5× 128 0.8× 69 0.5× 106 0.8× 27 694
Montserrat Lara‐Velazquez 250 0.9× 95 0.5× 103 0.6× 249 1.8× 87 0.7× 28 647
David Altshuler 192 0.7× 80 0.5× 76 0.5× 246 1.8× 107 0.8× 22 568
Audrey Petit 244 0.9× 107 0.6× 108 0.7× 100 0.7× 115 0.9× 26 695
Venkateswara Rao Gogineni 218 0.8× 116 0.7× 86 0.5× 57 0.4× 107 0.8× 24 562
Amir Barzegar Behrooz 382 1.4× 183 1.0× 62 0.4× 116 0.8× 159 1.3× 34 667
Mahshid Saleh 204 0.8× 119 0.7× 48 0.3× 295 2.1× 179 1.4× 22 662
Giulia Battafarano 282 1.0× 147 0.8× 65 0.4× 81 0.6× 88 0.7× 26 648
Eduard B. Dinca 250 0.9× 99 0.6× 39 0.2× 284 2.1× 111 0.9× 17 655
Keita Togashi 351 1.3× 104 0.6× 54 0.3× 198 1.4× 216 1.7× 38 667

Countries citing papers authored by Jun‐ichiro Kuroda

Since Specialization
Citations

This map shows the geographic impact of Jun‐ichiro Kuroda'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 Jun‐ichiro Kuroda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun‐ichiro Kuroda more than expected).

Fields of papers citing papers by Jun‐ichiro Kuroda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐ichiro Kuroda. 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 Jun‐ichiro Kuroda. The network helps show where Jun‐ichiro Kuroda may publish in the future.

Co-authorship network of co-authors of Jun‐ichiro Kuroda

This figure shows the co-authorship network connecting the top 25 collaborators of Jun‐ichiro Kuroda. A scholar is included among the top collaborators of Jun‐ichiro Kuroda based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jun‐ichiro Kuroda. Jun‐ichiro Kuroda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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