Malcolm Hayes

91 papers receiving 3.1k citations

Malcolm Hayes's Hit Papers

Ki67 in breast cancer: prognostic and predictive potential 2010 · 899 citations
8990+5+10Years since publication250500750

Peers

Malcolm Hayes
Comparison fields: 5 of 116
  • Cancer Research 1.2k
  • Pathology and Forensic Medicine 943
  • Oncology 1.4k
  • Dermatology 368
  • Pulmonary and Respiratory Medicine 626
Replace Eun Yoon Cho with:
Eun Yoon Cho South Korea
Hadi Yaziji United States
Tibor Tot Sweden
Ashley Cimino‐Mathews United States
Chang‐Ok Suh South Korea
B Zafrani France
Yun Gong United States
Aleš Ryška Czechia
Hideo Inaji Japan
Roland Penzel Germany
Malcolm Hayes relative to Eun Yoon Cho South Korea Eun Yoon Cho's profile →
Citations per field
00.5×1.5×
Eun Yoon Cho · 1×
Citations per year

Countries citing papers authored by Malcolm Hayes

Since Specialization
Citations

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

Fields of papers citing papers by Malcolm Hayes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Ki67 in breast cancer: prognostic and predictive potential
Hit paper breakdown →
2010899
2 2001177
3 2004163
4 2004116
5 2007104
6 2009100
7 200495
8 200393
9 200587
10 201885
11 200677
12 199669
13 201153
14 199851
15 199546
16 201344
17 200441
18 200036
19 201035
20 200834

About Malcolm Hayes

Malcolm Hayes is a scholar working on Oncology, Cancer Research, Pathology and Forensic Medicine, Pulmonary and Respiratory Medicine and Dermatology, having authored 92 papers that have together received 3.2k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (28 papers), Cancer and Skin Lesions (20 papers), Breast Lesions and Carcinomas (19 papers), HER2/EGFR in Cancer Research (9 papers), Salivary Gland Tumors Diagnosis and Treatment (9 papers), Sarcoma Diagnosis and Treatment (8 papers), Metastasis and carcinoma case studies (6 papers) and Cancer Cells and Metastasis (5 papers). The work is most often cited by research in Cancer Research (1.2k citations), Pathology and Forensic Medicine (943 citations), Oncology (1.4k citations), Dermatology (368 citations) and Pulmonary and Respiratory Medicine (626 citations). Malcolm Hayes has collaborated with scholars based in Canada, United States and South Africa. Frequent co-authors include Karen A. Gelmon, Rinat Yerushalmi, Peter M. Ravdin, Ryan Woods, Nikita Makretsov, Stephen Chia, David G. Huntsman, Ivo A. Olivotto, C. Blake Gilks and Thomas A. Thomson. Their work appears in journals such as Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin, Journal of Clinical Oncology, Cancer, Diagnostic Cytopathology and The American Journal of Surgical Pathology.

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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