Noboru Hamada

96 papers receiving 2k citations

Peers

Noboru Hamada
Comparison fields: 5 of 83
  • Endocrinology, Diabetes and Metabolism 1.1k
  • Discrete Mathematics and Combinatorics 176
  • Artificial Intelligence 530
  • Pathology and Forensic Medicine 227
  • Computational Theory and Mathematics 71
Replace Sun-Woo Kim with:
Sun-Woo Kim South Korea
Zhihong Wang China
Jianjun Dong China
Adam M. Smiles United States
Zhih‐Cherng Chen Taiwan
Laure Hélène Noël France
Komuraiah Myakala United States
Herbert S Chase United States
Lin Lü China
Masaki Makino Japan
Noboru Hamada relative to Sun-Woo Kim South Korea Sun-Woo Kim's profile →
Citations per field
00.5×10×20×30×35.3×
Sun-Woo Kim · 1×
Citations per year

Countries citing papers authored by Noboru Hamada

Since Specialization
Citations

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

Fields of papers citing papers by Noboru Hamada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Noboru Hamada, 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 Noboru Hamada Line = papers co-authored together Noboru Hamada links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 99 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007227
2 1984190
3 1985171
4 1982132
5 197387
6 200087
7 201287
8 199376
9 200169
10 198565
11 201259
12 197556
13 196852
14 197846
15 198746
16 201044
17
CHARACTERIZATION OF MIN-HYPERS IN A FINITE PROJECTIVE GEOMETRY AND ITS APPLICATIONS TO ERROR-CORRECTING CODES
198737
18 200637
19 201032
20 198931

About Noboru Hamada

Noboru Hamada is a scholar working on Endocrinology, Diabetes and Metabolism, Artificial Intelligence, Discrete Mathematics and Combinatorics, Pathology and Forensic Medicine and Geometry and Topology, having authored 99 papers that have together received 2.3k indexed citations. Recurring topics across this work include Coding theory and cryptography (38 papers), Thyroid Disorders and Treatments (37 papers), Advanced Combinatorial Mathematics (8 papers), Finite Group Theory Research (4 papers), Mathematics and Applications (3 papers), Ophthalmology and Eye Disorders (3 papers), Vitamin D Research Studies (3 papers) and Thyroid and Parathyroid Surgery (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.1k citations), Discrete Mathematics and Combinatorics (176 citations), Artificial Intelligence (530 citations), Pathology and Forensic Medicine (227 citations) and Computational Theory and Mathematics (71 citations). Noboru Hamada has collaborated with scholars based in Japan, Norway and United States. Frequent co-authors include Kunihiko Ito, Jaeduk Yoshimura Noh, Naoko Momotani, Luc Portmann, Takashi Mimura, G. Heinrich, Tor Helleseth, Yasuyuki Okamoto, Hirotoshi Nakamura and Akira Miyauchi. Their work appears in journals such as Journal of Statistical Planning and Inference, The Journal of Clinical Endocrinology & Metabolism, Discrete Mathematics, European Journal of Endocrinology and Hiroshima Mathematical Journal.

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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