Shinya Sugiyama

462 citations
18 papers · 348 indexed · h-index 10
Topics
Radiomics and Machine Learning in Medical Imaging (5 papers)Head and Neck Cancer Studies (5 papers)Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (4 papers)

In The Last Decade

Shinya Sugiyama

17 papers receiving 344 citations

Peers

Shinya Sugiyama
Comparison fields: 5 of 94
  • Pulmonary and Respiratory Medicine 125
  • Radiology, Nuclear Medicine and Imaging 86
  • Physiology 71
  • Infectious Diseases 61
  • Epidemiology 53
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Citations per field
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Citations per year

Countries citing papers authored by Shinya Sugiyama

Since Specialization
Citations

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

Fields of papers citing papers by Shinya Sugiyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shinya Sugiyama

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 6
2 45
3 9
4 23
5 28
6 9
7 90
8 0
9 56
10
Clinical characteristics classified by the serum KL-6 level in patients with organizing pneumonia.
3
11 11
12 21
13 4
14
[The changes in lymphocytes subpopulations of a patient with postoperative chylothorax].
6
15
Characteristics of lung cancer in the elderly.
14
16 1
17 4
18
[New chemotherapeutic method for the treatment of tracheal and bronchial cancers--nebulization chemotherapy].
18

About Shinya Sugiyama

Shinya Sugiyama is a scholar working on Otorhinolaryngology, Pulmonary and Respiratory Medicine and Radiation, having authored 18 papers that have together received 348 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Head and Neck Cancer Studies (5 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (4 papers). The work is most often cited by research in Health Informatics (12 citations), Otorhinolaryngology (23 citations) and Biological Psychiatry (13 citations). Shinya Sugiyama has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Makiko Ozawa, Yasuhisa Ano, Hiroyuki Nakayama, Aruto Yoshida, Kazuyuki Uchida, Todd McNutt, Yasuhiro Setoguchi, Yuta Kono, Seiko Soeda and Satoshi Kasagi. Their work appears in journals such as PLoS ONE, International Journal of Radiation Oncology*Biology*Physics and Electroencephalography and Clinical Neurophysiology.

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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