Tetsuya Yagi

5.1k citations
132 papers · 3.5k indexed · h-index 31

Impact in

Papers in

Tetsuya Yagi

124 papers receiving 3.4k citations

Peers

Tetsuya Yagi
Comparison fields: 5 of 134
  • Molecular Medicine 1.8k
  • Applied Microbiology and Biotechnology 420
  • Endocrinology 848
  • Infectious Diseases 861
  • Clinical Biochemistry 252
Replace Deniz Gür with:
Deniz Gür Türkiye
Patricia Winokur United States
Keigo Shibayama Japan
Georgia Vrioni Greece
Niels Frimodt‐Møller Denmark
Amos Adler Israel
Yingchun Xu China
Mary Motyl United States
Hanna E. Sidjabat Australia
Paul‐Louis Woerther France
Tetsuya Yagi relative to Deniz Gür Türkiye Deniz Gür's profile →
Citations per field
00.5×1.5×2.1×
Deniz Gür · 1×
Citations per year

Countries citing papers authored by Tetsuya Yagi

Since Specialization
Citations

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

Fields of papers citing papers by Tetsuya Yagi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20240
4 20240
5 20224
6 20222
7 20223
8 20213
9 20219
10 20182
11 20184
12 201715
13 201618
14 20163
15 20143
16 201219
17
20101
18 2003171
19
[New quinolone versus vancomycin/tobramycin for intestinal sterilization in patients who undergo allogeneic bone marrow transplantation].
19991
20
[Automatic assessment of left ventricular cavity area by the automated contour tracking method].
19964

About Tetsuya Yagi

Tetsuya Yagi is a scholar working on Applied Microbiology and Biotechnology, Molecular Medicine, Endocrinology, Infectious Diseases and Clinical Biochemistry, having authored 132 papers that have together received 3.5k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (40 papers), Mycobacterium research and diagnosis (22 papers), Tuberculosis Research and Epidemiology (19 papers), Antibiotic Use and Resistance (18 papers), Pneumonia and Respiratory Infections (15 papers), Antibiotics Pharmacokinetics and Efficacy (14 papers), Bacterial Identification and Susceptibility Testing (13 papers) and Antimicrobial Resistance in Staphylococcus (11 papers). The work is most often cited by research in Molecular Medicine (1.8k citations), Applied Microbiology and Biotechnology (420 citations), Endocrinology (848 citations), Infectious Diseases (861 citations) and Clinical Biochemistry (252 citations). Tetsuya Yagi has collaborated with scholars based in Japan, United States and Singapore. Frequent co-authors include Yoshichika Arakawa, Naohiro Shibata, Keigo Shibayama, Hiroshi Kurokawa, Yohei Doi, Kunikazu Yamane, Haru Kato, Keiko Yokoyama, Hiroshi Fujiwara and Masafumi Goto. Their work appears in journals such as Antimicrobial Agents and Chemotherapy, Journal of Clinical Microbiology, Biological and Pharmaceutical Bulletin, Open Forum Infectious Diseases and PLoS ONE.

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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