Suzanne Parry

38 papers receiving 1.6k citations

Peers

Suzanne Parry
Comparison fields: 5 of 92
  • Cancer Research 609
  • Dermatology 280
  • Oncology 739
  • Pathology and Forensic Medicine 478
  • Molecular Biology 652
Replace Sadako Akashi‐Tanaka with:
Sadako Akashi‐Tanaka Japan
Laura Fulford United Kingdom
Maria J. Worsham United States
Lorenza Pecciarini Italy
Muzaffar Akram United States
Takashi Hojo Japan
Hannah Y. Wen United States
Holger Dieterich Switzerland
Debra M. Lillington United Kingdom
Jens Packeisen Germany
Suzanne Parry relative to Sadako Akashi‐Tanaka Japan Sadako Akashi‐Tanaka's profile →
Citations per field
00.5×1.5×
Sadako Akashi‐Tanaka · 1×
Citations per year

Countries citing papers authored by Suzanne Parry

Since Specialization
Citations

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

Fields of papers citing papers by Suzanne Parry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004202
2 2005200
3 2009132
4 2008115
5 200289
6 201280
7 200776
8 200765
9 200461
10 200856
11 200956
12 200853
13 201041
14 201841
15 200635
16 200734
17 200932
18 201330
19 201627
20 200727

About Suzanne Parry

Suzanne Parry is a scholar working on Oncology, Molecular Biology, Cancer Research, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging, having authored 44 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (8 papers), HER2/EGFR in Cancer Research (7 papers), Breast Cancer Treatment Studies (7 papers), Breast Lesions and Carcinomas (6 papers), Cancer Genomics and Diagnostics (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Cancer and Skin Lesions (5 papers) and Genetic factors in colorectal cancer (4 papers). The work is most often cited by research in Cancer Research (609 citations), Dermatology (280 citations), Oncology (739 citations), Pathology and Forensic Medicine (478 citations) and Molecular Biology (652 citations). Suzanne Parry has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Jorge S. Reis‐Filho, Sunil R. Lakhani, Kay Savage, Peter T. Simpson, Chris Jones, Caterina Marchiò, Alan Mackay, Sarah E. Pinder, Alan Ashworth and Betania Mahler‐Araujo. Their work appears in journals such as The Journal of Pathology, The American Journal of Surgical Pathology, Journal of Clinical Pathology, The Journal of Pathology Clinical Research and Cancer Research.

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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