Masayuki Tsuneki

2.3k citations
51 papers · 1.5k indexed · 1 hit paper · h-index 22

Masayuki Tsuneki

50 papers receiving 1.4k citations

Hit Papers

Deep Learning Models for Histopathological Classification...271202020262022202450100150200250

Peers

Masayuki Tsuneki
Comparison fields: 5 of 128
  • Health Informatics 42
  • Radiology, Nuclear Medicine and Imaging 439
  • Oral Surgery 131
  • Emergency Medical Services 122
  • Artificial Intelligence 524
Replace Christian Freudlsperger with:
Christian Freudlsperger Germany
Mark W. El‐Deiry United States
Alhadi Almangush Finland
Mohammadhadi Bagheri United States
Paulo Rogério de Faria Brazil
Hak Hee Kim South Korea
Stephan Wienert Germany
Arvydas Laurinavičius Lithuania
Markus Eckstein Germany
Masayuki Tsuneki relative to Christian Freudlsperger Germany Christian Freudlsperger's profile →
Citations per field
00.5×10×15.3×
Christian Freudlsperger · 1×
Citations per year

Countries citing papers authored by Masayuki Tsuneki

Since Specialization
Citations

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

Fields of papers citing papers by Masayuki Tsuneki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Masayuki Tsuneki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Masayuki Tsuneki Line = papers co-authored together Masayuki Tsuneki links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20234
4 202311
5 20227
6 202245
7 20227
8 2022117
9 202139
10
Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumoursbreakdown →
2020271
11 20195
12 201729
13 201622
14 20159
15 201219
16 201233
17 201026
18 200931
19 200840
20 20076

About Masayuki Tsuneki

Masayuki Tsuneki is a scholar working on Oral Surgery, Oncology and Cell Biology, having authored 51 papers that have together received 1.5k indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Colorectal Cancer Screening and Detection (9 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Oral and Maxillofacial Pathology (7 papers), Hippo pathway signaling and YAP/TAZ (6 papers), Lymphatic System and Diseases (5 papers), Proteoglycans and glycosaminoglycans research (5 papers) and Salivary Gland Tumors Diagnosis and Treatment (5 papers). The work is most often cited by research in Health Informatics (42 citations), Radiology, Nuclear Medicine and Imaging (439 citations) and Oral Surgery (131 citations). Masayuki Tsuneki has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Fahdi Kanavati, Joseph A. Madri, Osamu Iizuka, Koji Arihiro, Kei Kato, Satoshi Maruyama, Takashi Saku, Jun Cheng, Manabu Yamazaki and Koji Yamazaki. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and Molecular and Cellular Biology.

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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