Hitoshi Iyatomi

4.4k total citations
87 papers, 2.9k citations indexed

About

Hitoshi Iyatomi is a scholar working on Oncology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hitoshi Iyatomi has authored 87 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Oncology, 37 papers in Artificial Intelligence and 19 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hitoshi Iyatomi's work include Cutaneous Melanoma Detection and Management (36 papers), AI in cancer detection (20 papers) and Optical Coherence Tomography Applications (13 papers). Hitoshi Iyatomi is often cited by papers focused on Cutaneous Melanoma Detection and Management (36 papers), AI in cancer detection (20 papers) and Optical Coherence Tomography Applications (13 papers). Hitoshi Iyatomi collaborates with scholars based in Japan, United States and United Kingdom. Hitoshi Iyatomi's co-authors include M. Emre Celebi, William V. Stoecker, Gerald Schaefer, Y. Alp Aslandogan, Randy H. Moss, Hassan A. Kingravi, Masaru Tanaka, Hiroshi Oka, Masafumi Hagiwara and K. Ogawa and has published in prestigious journals such as PLoS ONE, IEEE Access and Journal of Investigative Dermatology.

In The Last Decade

Hitoshi Iyatomi

83 papers receiving 2.7k citations

Peers

Hitoshi Iyatomi
Comparison fields: 5 of 115
  • Oncology 2.2k
  • Artificial Intelligence 1.6k
  • Biomedical Engineering 610
  • Epidemiology 536
  • Computer Vision and Pattern Recognition 443
Replace Randy H. Moss with:
Randy H. Moss United States
Y. Alp Aslandogan United States
Muhammad Sharif Pakistan
İshak Paçal Türkiye
Parvathaneni Naga Srinivasu India
M. Aldeen Australia
Giuseppe Di Leo Italy
Zhenkun Wen China
Shan E Ahmed Raza United Kingdom
Md Mamunur Rahaman China
Randy H. Moss United States View profile →
Citations per field, relative to Hitoshi Iyatomi
Hitoshi Iyatomi · 1×
Citations per year, relative to Hitoshi Iyatomi
Hitoshi Iyatomi · 1×

Countries citing papers authored by Hitoshi Iyatomi

Since Specialization
Citations

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

Fields of papers citing papers by Hitoshi Iyatomi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hitoshi Iyatomi

This figure shows the co-authorship network connecting the top 25 collaborators of Hitoshi Iyatomi. A scholar is included among the top collaborators of Hitoshi Iyatomi 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 Hitoshi Iyatomi. Hitoshi Iyatomi 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
# Work Indexed citations
1 1
2 0
3 9
4 2
5 1
6 4
7 1
8 1
9 15
10 2
11 94
12 14
13 30
14 18
15 31
16 9
17 60
18 133
19 1
20
Additional Learning Framework for Multipurpose Image Recognition
2

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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