M Kashimura

66 papers receiving 1.1k citations

Peers

M Kashimura
Comparison fields: 5 of 100
  • Obstetrics and Gynecology 246
  • Genetics 138
  • Hematology 139
  • Oncology 302
  • Pathology and Forensic Medicine 182
Replace Tamio Koizumi with:
Tamio Koizumi Japan
Mai He United States
David Cantú de León Mexico
Bart Wagner United Kingdom
Dorit Blickstein Israel
Jongkolnee Settakorn Thailand
S. M. Sieber United States
Orla Maguire United States
Marek Spaczyński Poland
M A Forbes United Kingdom
M Kashimura relative to Tamio Koizumi Japan Tamio Koizumi's profile →
Citations per field
00.5×5.7×
Tamio Koizumi · 1×
Citations per year

Countries citing papers authored by M Kashimura

Since Specialization
Citations

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

Fields of papers citing papers by M Kashimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201190
2 200883
3 200680
4 201076
5 199963
6 199959
7 200357
8 200153
9 200753
10 199543
11 202041
12 199938
13 200727
14 198526
15 201026
16
Study of dose escalation and sequence switching of administration of the combination of docetaxel and doxorubicin in advanced breast cancer.
200025
17 200324
18 200821
19 199920
20 199017

About M Kashimura

M Kashimura is a scholar working on Molecular Biology, Oncology, Obstetrics and Gynecology, Epidemiology and Pathology and Forensic Medicine, having authored 71 papers that have together received 1.2k indexed citations. Recurring topics across this work include Endometrial and Cervical Cancer Treatments (10 papers), Lymphoma Diagnosis and Treatment (9 papers), Viral-associated cancers and disorders (7 papers), Chronic Lymphocytic Leukemia Research (5 papers), Cervical Cancer and HPV Research (5 papers), Acute Myeloid Leukemia Research (4 papers), Eosinophilic Disorders and Syndromes (4 papers) and Gestational Trophoblastic Disease Studies (4 papers). The work is most often cited by research in Obstetrics and Gynecology (246 citations), Genetics (138 citations), Hematology (139 citations), Oncology (302 citations) and Pathology and Forensic Medicine (182 citations). M Kashimura has collaborated with scholars based in Japan and United States. Frequent co-authors include Naoyuki Toki, H Nanri, Masaharu Ikeda, Kuniaki Ejima, Tsuneo Fujita, Toshinori Kawagoe, M Tanaka, Yutaka Matsuura, Masaru Kojima and Eiji Shibata. Their work appears in journals such as Placenta, American Journal of Hematology, International Journal of Gynecological Cancer, International Journal of STD & AIDS and Annals of Oncology.

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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