Takuro Horikoshi

733 citations
53 papers · 440 indexed · h-index 12
Topics
Radiomics and Machine Learning in Medical Imaging (6 papers)Autopsy Techniques and Outcomes (5 papers)Radiation Dose and Imaging (5 papers)
Partner nations
JapanUnited States

In The Last Decade

Takuro Horikoshi

52 papers receiving 434 citations

Peers

Takuro Horikoshi
Comparison fields: 5 of 83
  • Radiology, Nuclear Medicine and Imaging 173
  • Surgery 102
  • Pulmonary and Respiratory Medicine 100
  • Neurology 88
  • Biomedical Engineering 51
Replace Sundeep M. Nayak with:
Sundeep M. Nayak United States
Thierry A. G. M. Huisman Switzerland
Wulin Tan China
Kavous Firouznia Iran
Yoshimitsu Ohgiya Japan
Sıla Ulus Türkiye
Asthik Biswas United Kingdom
Stephan Waldeck Germany
Ursula Nemec Austria
Takuro Horikoshi relative to Sundeep M. Nayak United States Sundeep M. Nayak's profile →
Citations per field
00.5×4.5×
Sundeep M. Nayak · 1×
Citations per year

Countries citing papers authored by Takuro Horikoshi

Since Specialization
Citations

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

Fields of papers citing papers by Takuro Horikoshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takuro Horikoshi

This figure shows the co-authorship network connecting the top 25 collaborators of Takuro Horikoshi. A scholar is included among the top collaborators of Takuro Horikoshi 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 Takuro Horikoshi. Takuro Horikoshi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2 1
3 1
4 1
5 5
6 1
7 21
8 8
9 8
10 5
11 11
12 28
13 6
14 6
15 9
16 6
17 3
18 11
19 8
20 8

About Takuro Horikoshi

Takuro Horikoshi is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Internal Medicine, having authored 53 papers that have together received 440 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Autopsy Techniques and Outcomes (5 papers) and Radiation Dose and Imaging (5 papers). The work is most often cited by research in Health Informatics (11 citations), Radiology, Nuclear Medicine and Imaging (173 citations) and Neurology (88 citations). Takuro Horikoshi has collaborated with scholars based in Japan and United States. Frequent co-authors include Hajime Yokota, Takashi Uno, Hisao Ito, Ryota Shimofusa, Seiji Yamamoto, Hiroki Suyari, Satoshi Kuwabara, Hiroki Mukai, Hirotaro Iwase and Yoshihiro Kubota. Their work appears in journals such as Journal of the American College of Cardiology, PLoS ONE and Scientific Reports.

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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