Kazutaka Jin

1.9k citations
103 papers · 1.3k indexed · h-index 20

Kazutaka Jin

92 papers receiving 1.2k citations

Peers

Kazutaka Jin
Comparison fields: 5 of 104
  • Psychiatry and Mental health 608
  • Cognitive Neuroscience 380
  • Neurology 285
  • Cellular and Molecular Neuroscience 262
  • Neurology 108
Replace Neelan Pillay with:
Neelan Pillay Canada
Serap Saygı Türkiye
Ashalatha Radhakrishnan India
Carlo Di Bonaventura Italy
Antonio Donaire Spain
Brien Smith United States
Amiram Katz United States
Anna Teresa Giallonardo Italy
Yong D. Park United States
Hsiang‐Yu Yu Taiwan
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Citations per field
00.5×1.5×1.9×
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Citations per year

Countries citing papers authored by Kazutaka Jin

Since Specialization
Citations

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

Fields of papers citing papers by Kazutaka Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20243
4 20240
5 20243
6 20230
7 20232
8 202118
9
Evaluating the Effect of Cryptorchidism on Clinical Stage of Testicular Seminoma
20200
10
Absolute Counts of Peripheral Lymphocyte Subsets Correlate with the Progression-Free Survival and Metastatic Status of Pancreatic Neuroendocrine Tumour Patients
20200
11 20206
12 20204
13
The CRP/Albumin Ratio Predicts Survival And Monitors Chemotherapeutic Effectiveness In Patients With Advanced Pancreatic Cancer
20192
14 201930
15 20182
16 20183
17 20177
18
Decreased miR-503 expression in gastric cancer is inversely correlated with serum carcinoembryonic antigen and acts as a potential prognostic and diagnostic biomarker
20164
19 201221
20 200438

About Kazutaka Jin

Kazutaka Jin is a scholar working on Psychiatry and Mental health, Cognitive Neuroscience and Pediatrics, Perinatology and Child Health, having authored 103 papers that have together received 1.3k indexed citations. Recurring topics across this work include Epilepsy research and treatment (55 papers), EEG and Brain-Computer Interfaces (24 papers), Neonatal and fetal brain pathology (17 papers), Neuroscience and Neuropharmacology Research (17 papers), Pharmacological Effects and Toxicity Studies (17 papers), Neurobiology of Language and Bilingualism (6 papers), Neural dynamics and brain function (5 papers) and Functional Brain Connectivity Studies (5 papers). The work is most often cited by research in Psychiatry and Mental health (608 citations), Cognitive Neuroscience (380 citations) and Neurology (285 citations). Kazutaka Jin has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Nobukazu Nakasato, Yosuke Kakisaka, Masaki Iwasaki, Teiji Tominaga, Yasuto Itoyama, Richard C. Burgess, John C. Mosher, Andreas V. Alexopoulos, Dileep Nair and Masashi Aoki. Their work appears in journals such as SHILAP Revista de lepidopterología, Neurology and Scientific Reports.

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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