Masayuki Nitta

5.0k citations
94 papers · 3.7k indexed · 2 hit papers · h-index 26
Topics
Glioma Diagnosis and Treatment (53 papers)Meningioma and schwannoma management (22 papers)Radiomics and Machine Learning in Medical Imaging (11 papers)

In The Last Decade

Masayuki Nitta

85 papers receiving 3.7k citations

Hit Papers

Cytokinesis failure generating tetraploids promotes tumor...200320262010201820052003250500750

Peers

Masayuki Nitta
Comparison fields: 5 of 115
  • Molecular Biology 1.9k
  • Cell Biology 1.6k
  • Oncology 950
  • Genetics 734
  • Pulmonary and Respiratory Medicine 497
Replace Takashi Sasayama with:
Takashi Sasayama Japan
Candece L. Gladson United States
Patricia H. Warne United Kingdom
Keishi Makino Japan
Per Øyvind Enger Norway
Anna Lasorella United States
Pablo Rodriguez‐Viciana United States
Masayuki Komada Japan
Cláudio A. Franco Portugal
Gerald C. Chu United States
Masayuki Nitta relative to Takashi Sasayama Japan Takashi Sasayama's profile →
Citations per field
00.5×1.5×
Takashi Sasayama · 1×
Citations per year

Countries citing papers authored by Masayuki Nitta

Since Specialization
Citations

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

Fields of papers citing papers by Masayuki Nitta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masayuki Nitta

This figure shows the co-authorship network connecting the top 25 collaborators of Masayuki Nitta. A scholar is included among the top collaborators of Masayuki Nitta 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 Masayuki Nitta. Masayuki Nitta 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 2
2 0
3 1
4 3
5 11
6 10
7 67
8 3
9 20
10 10
11 2
12 6
13 42
14 39
15 60
16 34
17 296
18 20
19 41
20 73

About Masayuki Nitta

Masayuki Nitta is a scholar working on Genetics, Structural Biology and Radiology, Nuclear Medicine and Imaging, having authored 94 papers that have together received 3.7k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (53 papers), Meningioma and schwannoma management (22 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). The work is most often cited by research in Cell Biology (1.6k citations), Genetics (734 citations) and Oncology (950 citations). Masayuki Nitta has collaborated with scholars based in Japan, United States and Czechia. Frequent co-authors include Hideyuki Saya, David Pellman, Roderick T. Bronson, Elena V. Ivanova, Madhavi Bandi, Takeshi Fujiwara, Toru Hirota, Tomotoshi Marumoto, Yoshihiro Muragaki and Takashi Maruyama. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

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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