T. Kadota

1.1k citations
86 papers · 854 indexed · h-index 15
Topics
Cancer therapeutics and mechanisms (10 papers)Blind Source Separation Techniques (8 papers)Distributed Sensor Networks and Detection Algorithms (8 papers)

In The Last Decade

T. Kadota

77 papers receiving 664 citations

Peers

T. Kadota
Comparison fields: 5 of 115
  • Computer Networks and Communications 172
  • Artificial Intelligence 148
  • Electrical and Electronic Engineering 139
  • Molecular Biology 107
  • Oncology 92
Replace Frederick J. Beutler with:
Frederick J. Beutler United States
K. Srinivasa Rao India
S. P. Lloyd Australia
Raisa E. Feldman United States
Josef Leydold Austria
A. G. Miamee United States
Arnaud Durand France
Philippe Rigollet United States
R. Lugannani United States
B. W. Stuck United States
T. Kadota relative to Frederick J. Beutler United States Frederick J. Beutler's profile →
Citations per field
00.5×10×20×30×40×46×
Frederick J. Beutler · 1×
Citations per year

Countries citing papers authored by T. Kadota

Since Specialization
Citations

This map shows the geographic impact of T. Kadota'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 T. Kadota with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Kadota more than expected).

Fields of papers citing papers by T. Kadota

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Kadota

This figure shows the co-authorship network connecting the top 25 collaborators of T. Kadota. A scholar is included among the top collaborators of T. Kadota 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 T. Kadota. T. Kadota 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 15
2 58
3 11
4 13
5 3
6 8
7
General Consideration for Assessment of No-Observed Adverse Effect Level(NOAEL)
1
8 4
9 1
10 15
11 1
12 2
13 4
14
1
15
1
16 1
17 6
18 1
19 7
20 2

About T. Kadota

T. Kadota is a scholar working on Clinical Biochemistry, Signal Processing and Developmental Neuroscience, having authored 86 papers that have together received 854 indexed citations. Recurring topics across this work include Cancer therapeutics and mechanisms (10 papers), Blind Source Separation Techniques (8 papers) and Distributed Sensor Networks and Detection Algorithms (8 papers). The work is most often cited by research in Statistics and Probability (72 citations), Signal Processing (87 citations) and Computer Networks and Communications (172 citations). T. Kadota has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include L. A. Shepp, J. Ziv, Moshe Zakai, Takao Yamori, Shigeo Sato, A.D. Wyner, Shigeo Kawano, E. N. Gilbert, Hisashi KOHMURA and D. Slepian. Their work appears in journals such as IEEE Transactions on Information Theory, European Journal of Pharmacology and IEEE Transactions on Software Engineering.

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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