M.S. Kao

774 citations
22 papers · 579 indexed · h-index 13

M.S. Kao

21 papers receiving 561 citations

Peers

M.S. Kao
Comparison fields: 5 of 66
  • Obstetrics and Gynecology 400
  • Reproductive Medicine 212
  • Epidemiology 163
  • Surgery 170
  • Pathology and Forensic Medicine 66
Replace J. A. Lejárcegui with:
J. A. Lejárcegui Spain
Sakae HATA Japan
Trudy R. Baker United States
M. Tiffany United Kingdom
Jaroslav Klát Czechia
Howard D. Homesley United States
Sang‐Young Ryu South Korea
Lynn D. Kowalski United States
Jaime Coronel Mexico
Lucía González‐Cortijo Spain
M.S. Kao relative to J. A. Lejárcegui Spain J. A. Lejárcegui's profile →
Citations per field
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J. A. Lejárcegui · 1×
Citations per year

Countries citing papers authored by M.S. Kao

Since Specialization
Citations

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

Fields of papers citing papers by M.S. Kao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201011
2 20091
3 20066
4 20039
5 200015
6 199510
7
Resistance to cytolysis by tumor necrosis factor alpha in malignant gynecological cell lines is associated with the expression of protein(s) that prevent the activation of phospholipase A2 by tumor necrosis factor alpha.
199232
8
Expression of a resistance mechanism in ovarian and cervical carcinoma cells prevents their lysis by gamma-interferon.
199010
9 19907
10 198926
11 198963
12 198867
13 198814
14 198744
15 198755
16 198712
17 198670
18 19861
19 198541
20 198016

About M.S. Kao

M.S. Kao is a scholar working on Obstetrics and Gynecology, Reproductive Medicine, Radiation, Toxicology and Oncology, having authored 22 papers that have together received 579 indexed citations. Recurring topics across this work include Endometrial and Cervical Cancer Treatments (12 papers), Ovarian cancer diagnosis and treatment (8 papers), Cervical Cancer and HPV Research (5 papers), Advanced Radiotherapy Techniques (3 papers), Uterine Myomas and Treatments (3 papers), Testicular diseases and treatments (2 papers), Intraperitoneal and Appendiceal Malignancies (2 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Obstetrics and Gynecology (400 citations), Reproductive Medicine (212 citations), Epidemiology (163 citations), Surgery (170 citations) and Pathology and Forensic Medicine (66 citations). M.S. Kao has collaborated with scholars based in United States, Ireland and Belgium. Frequent co-authors include H. Marvin Camel, Andrew E. Galakatos, Perry W. Grigsby, Carlos A. Pérez, Robert R. Kuske, Mary Ann Hederman, Carlos A. Perez, John Leslie Collins, Carlos A. Perez and Allan J. Jacobs. Their work appears in journals such as Gynecologic Oncology, International Journal of Radiation Oncology*Biology*Physics, Cancer, Radiotherapy and Oncology and Radiology.

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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