Tokiko Endo

248 total papers · 2.2k total citations
118 papers, 1.4k citations indexed

About

Tokiko Endo is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Tokiko Endo has authored 118 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Artificial Intelligence, 41 papers in Radiology, Nuclear Medicine and Imaging and 34 papers in Oncology. Recurrent topics in Tokiko Endo's work include AI in cancer detection (49 papers), Digital Radiography and Breast Imaging (21 papers) and Radiomics and Machine Learning in Medical Imaging (20 papers). Tokiko Endo is often cited by papers focused on AI in cancer detection (49 papers), Digital Radiography and Breast Imaging (21 papers) and Radiomics and Machine Learning in Medical Imaging (20 papers). Tokiko Endo collaborates with scholars based in Japan, United States and China. Tokiko Endo's co-authors include Takeshi Hara, Hiroshi Fujita, Eriko Tohno, Mamoru Fukuda, Noriaki Ohuchi, Ichiro Tsuji, Takuji Iwase, Shu Ichihara, Takako Morita and Takanori Ishida and has published in prestigious journals such as The Lancet, Annals of Surgery and IEEE Transactions on Medical Imaging.

In The Last Decade

Tokiko Endo

99 papers receiving 1.3k citations

Hit Papers

Sensitivity and specifici... 2015 2026 2018 2022 2015 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Tokiko Endo 613 520 372 345 258 118 1.4k
Romain Modzelewski 329 0.5× 1.1k 2.1× 197 0.5× 503 1.5× 122 0.5× 70 1.8k
Sergi Ganau 660 1.1× 679 1.3× 210 0.6× 268 0.8× 175 0.7× 49 1.7k
Melcior Sentís 722 1.2× 754 1.4× 170 0.5× 190 0.6× 218 0.8× 62 1.6k
Sanjoy Chatterjee 260 0.4× 369 0.7× 416 1.1× 259 0.8× 67 0.3× 104 1.5k
Haydee Ojeda‐Fournier 550 0.9× 929 1.8× 262 0.7× 254 0.7× 253 1.0× 68 1.5k
Raffaella Massafra 531 0.9× 696 1.3× 235 0.6× 299 0.9× 87 0.3× 93 1.3k
Kazunori Kubota 420 0.7× 854 1.6× 201 0.5× 209 0.6× 145 0.6× 102 1.5k
Cherie M. Kuzmiak 311 0.5× 492 0.9× 277 0.7× 336 1.0× 198 0.8× 82 1.1k
Dana H. Whaley 442 0.7× 702 1.4× 279 0.8× 461 1.3× 144 0.6× 43 1.2k
Kanae K. Miyake 496 0.8× 792 1.5× 194 0.5× 212 0.6× 77 0.3× 59 1.3k

Countries citing papers authored by Tokiko Endo

Since Specialization
Citations

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

Fields of papers citing papers by Tokiko Endo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tokiko Endo

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