Tomoko Matsubara

47 total papers · 587 total citations
25 papers, 431 citations indexed

About

Tomoko Matsubara is a scholar working on Artificial Intelligence, Physiology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Tomoko Matsubara has authored 25 papers receiving a total of 431 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 7 papers in Physiology and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Tomoko Matsubara's work include AI in cancer detection (7 papers), Adipose Tissue and Metabolism (4 papers) and Digital Radiography and Breast Imaging (4 papers). Tomoko Matsubara is often cited by papers focused on AI in cancer detection (7 papers), Adipose Tissue and Metabolism (4 papers) and Digital Radiography and Breast Imaging (4 papers). Tomoko Matsubara collaborates with scholars based in Japan, United States and Vietnam. Tomoko Matsubara's co-authors include Nobuhiko Akazawa, Song‐Gyu Ra, Youngju Choi, Seiji Maeda, Huang Hu, Hiroshi Kumagai, Satoshi Oikawa, Brenton T. Laing, Asako Miyaki and Hiroshi Fujita and has published in prestigious journals such as PLoS ONE, Scientific Reports and Life Sciences.

In The Last Decade

Tomoko Matsubara

25 papers receiving 419 citations

Author Peers

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

Author Last Decade Papers Cites
Tomoko Matsubara 156 66 62 51 50 25 431
Pınar Akan 97 0.6× 89 1.3× 20 0.3× 14 0.3× 41 0.8× 37 493
Yu‐Che Tsai 91 0.6× 38 0.6× 80 1.3× 21 0.4× 135 2.7× 22 434
Jiahe Wang 79 0.5× 108 1.6× 9 0.1× 12 0.2× 5 0.1× 55 409
C. E. Thomsen 156 1.0× 62 0.9× 35 0.6× 21 0.4× 4 0.1× 21 372
Zhi Liu 72 0.5× 82 1.2× 35 0.6× 22 0.4× 3 0.1× 37 385
Zhe Wang 73 0.5× 147 2.2× 55 0.9× 14 0.3× 68 1.4× 25 469
Petr Karen 97 0.6× 157 2.4× 83 1.3× 10 0.2× 4 0.1× 42 465
Mikiko Kawaguchi 74 0.5× 67 1.0× 20 0.3× 7 0.1× 10 0.2× 29 374
Huanliang Wang 25 0.2× 111 1.7× 31 0.5× 14 0.3× 8 0.2× 27 460
Qun Huang 32 0.2× 108 1.6× 32 0.5× 20 0.4× 7 0.1× 26 421

Countries citing papers authored by Tomoko Matsubara

Since Specialization
Citations

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

Fields of papers citing papers by Tomoko Matsubara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoko Matsubara

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoko Matsubara. A scholar is included among the top collaborators of Tomoko Matsubara 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 Tomoko Matsubara. Tomoko Matsubara 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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