Ram Eitan

70 papers receiving 880 citations

Peers

Ram Eitan
Comparison fields: 5 of 61
  • Reproductive Medicine 320
  • Obstetrics and Gynecology 213
  • Cancer Research 138
  • Rheumatology 78
  • Oncology 100
Replace Kyo Won Lee with:
Kyo Won Lee South Korea
Valentin Kolev United States
Sara Imboden Switzerland
Liron Kogan Israel
Magali Provansal France
Golnar Rasty Canada
Anne M. van Altena Netherlands
Mario Valenzano Menada Italy
Stephen DePasquale United States
Lee‐Wen Huang Taiwan
Ram Eitan relative to Kyo Won Lee South Korea Kyo Won Lee's profile →
Citations per field
00.5×2.9×
Kyo Won Lee · 1×
Citations per year

Countries citing papers authored by Ram Eitan

Since Specialization
Citations

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

Fields of papers citing papers by Ram Eitan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009130
2 201279
3 200342
4 201542
5 200540
6 201240
7 201540
8 200734
9 201530
10 201524
11 201821
12 201521
13 201520
14 202020
15 201216
16 201316
17 201515
18 202015
19 201915
20 201915

About Ram Eitan

Ram Eitan is a scholar working on Reproductive Medicine, Obstetrics and Gynecology, Oncology, Public Health, Environmental and Occupational Health and Rheumatology, having authored 78 papers that have together received 905 indexed citations. Recurring topics across this work include Ovarian cancer diagnosis and treatment (26 papers), Endometrial and Cervical Cancer Treatments (23 papers), Pelvic floor disorders treatments (6 papers), Intraperitoneal and Appendiceal Malignancies (4 papers), Reproductive Biology and Fertility (4 papers), Ectopic Pregnancy Diagnosis and Management (3 papers), Inflammatory Biomarkers in Disease Prognosis (3 papers) and Endometriosis Research and Treatment (2 papers). The work is most often cited by research in Reproductive Medicine (320 citations), Obstetrics and Gynecology (213 citations), Cancer Research (138 citations), Rheumatology (78 citations) and Oncology (100 citations). Ram Eitan has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Yoav Peled, Haim Krissi, Hanoch Levavi, Gad Sabah, Richard R. Barakat, Oded Raban, Eran Ashwal‏, Ilan Bruchim, Liran Hiersch and Arnon Wiznitzer. Their work appears in journals such as Gynecologic Oncology, International Journal of Gynecological Cancer, European Journal of Obstetrics & Gynecology and Reproductive Biology, International Journal of Gynecology & Obstetrics and European Journal of Surgical 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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