Marjorie Green

5.8k total citations · 2 hit papers
15 papers, 4.1k citations indexed

About

Marjorie Green is a scholar working on Cancer Research, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Marjorie Green has authored 15 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cancer Research, 9 papers in Oncology and 6 papers in Pathology and Forensic Medicine. Recurrent topics in Marjorie Green's work include Breast Cancer Treatment Studies (10 papers), Breast Lesions and Carcinomas (6 papers) and HER2/EGFR in Cancer Research (4 papers). Marjorie Green is often cited by papers focused on Breast Cancer Treatment Studies (10 papers), Breast Lesions and Carcinomas (6 papers) and HER2/EGFR in Cancer Research (4 papers). Marjorie Green collaborates with scholars based in United States, France and Germany. Marjorie Green's co-authors include Gabriel N. Hortobágyi, W. Fraser Symmans, Lajos Pusztai, Bryan T. Hennessy, Kenneth R. Hess, Cornelia Liedtke, Ana M. González-Angulo, Chafika Mazouni, Fabrice André and Massimo Cristofanilli and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Clinical Oncology.

In The Last Decade

Marjorie Green

15 papers receiving 4.0k citations

Hit Papers

Response to Neoadjuvant Therapy and Long-Term Survival in... 2007 2026 2013 2019 2008 2007 500 1000 1.5k 2.0k

Peers

Marjorie Green
Comparison fields: 5 of 98
  • Cancer Research 2.5k
  • Oncology 2.5k
  • Molecular Biology 971
  • Pathology and Forensic Medicine 847
  • Pulmonary and Respiratory Medicine 650
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Maysa E. El‐Sayed United Kingdom
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Citations per field, relative to Marjorie Green
Marjorie Green · 1×
Citations per year, relative to Marjorie Green
Marjorie Green · 1×

Countries citing papers authored by Marjorie Green

Since Specialization
Citations

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

Fields of papers citing papers by Marjorie Green

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marjorie Green

This figure shows the co-authorship network connecting the top 25 collaborators of Marjorie Green. A scholar is included among the top collaborators of Marjorie Green 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 Marjorie Green. Marjorie Green is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
# Work Indexed citations
1 62
2 47
3 4
4 1
5 1
6 69
7
Response to Neoadjuvant Therapy and Long-Term Survival in Patients With Triple-Negative Breast Cancer breakdown →
2191
8 80
9
Measurement of Residual Breast Cancer Burden to Predict Survival After Neoadjuvant Chemotherapy breakdown →
1078
10 19
11 323
12 117
13
Neoadjuvant chemotherapy for operable breast cancer.
27
14 44
15 19

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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