David Gyorki

7.8k total citations · 1 hit paper
109 papers, 3.0k citations indexed

About

David Gyorki is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, David Gyorki has authored 109 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Oncology, 28 papers in Pulmonary and Respiratory Medicine and 25 papers in Molecular Biology. Recurrent topics in David Gyorki's work include Cutaneous Melanoma Detection and Management (43 papers), CAR-T cell therapy research (24 papers) and Sarcoma Diagnosis and Treatment (21 papers). David Gyorki is often cited by papers focused on Cutaneous Melanoma Detection and Management (43 papers), CAR-T cell therapy research (24 papers) and Sarcoma Diagnosis and Treatment (21 papers). David Gyorki collaborates with scholars based in Australia, United States and Switzerland. David Gyorki's co-authors include Geoffrey J. Lindeman, Jane E. Visvader, Marie-Liesse Asselin-Labat, Gordon K. Smyth, Di Wu, Teresa Ward, Stephen B. Fox, François Vaillant, Frank Feleppa and Bhupinder Pal and has published in prestigious journals such as Journal of Clinical Investigation, Nature Medicine and Journal of Clinical Oncology.

In The Last Decade

David Gyorki

104 papers receiving 2.9k citations

Hit Papers

Aberrant luminal progenit... 2009 2026 2014 2020 2009 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Gyorki Australia 22 2.1k 1.2k 577 532 459 109 3.0k
Josep M. Piulats Spain 30 1.5k 0.7× 1.1k 0.9× 894 1.5× 448 0.8× 847 1.8× 162 3.2k
Hetty E. Carraway United States 35 1.1k 0.5× 1.7k 1.5× 488 0.8× 399 0.8× 318 0.7× 212 3.6k
Asma Tulbah Saudi Arabia 31 1.9k 0.9× 880 0.8× 765 1.3× 837 1.6× 533 1.2× 104 3.3k
Thierry Lesimple France 32 2.0k 0.9× 1.2k 1.0× 416 0.7× 401 0.8× 1.0k 2.2× 139 3.3k
Konstantin J. Dedes Switzerland 25 1.1k 0.5× 1.3k 1.1× 372 0.6× 590 1.1× 357 0.8× 79 2.8k
Socorro Marıá Rodríguez-Pinilla Spain 30 2.0k 0.9× 1.6k 1.3× 421 0.7× 1.1k 2.0× 341 0.7× 97 3.8k
Stanley W. McCarthy Australia 35 2.5k 1.2× 1.6k 1.3× 628 1.1× 543 1.0× 453 1.0× 73 3.7k
Xinan Sheng China 30 2.2k 1.0× 1.5k 1.3× 736 1.3× 411 0.8× 493 1.1× 192 3.3k
J Garcı́a-Conde Spain 35 2.0k 1.0× 954 0.8× 596 1.0× 584 1.1× 425 0.9× 104 3.9k
Yan‐Gao Man United States 28 1.2k 0.6× 1.3k 1.1× 495 0.9× 1.1k 2.0× 382 0.8× 95 3.1k

Countries citing papers authored by David Gyorki

Since Specialization
Citations

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

Fields of papers citing papers by David Gyorki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Gyorki

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

All Works

20 of 20 papers shown
1.
Mor, Eyal, et al.. (2025). Defining an Unresectable Primary Retroperitoneal Sarcoma. ANZ Journal of Surgery. 95(12). 2489–2496.
2.
Vargas, Ana Cristina, Fiona Maclean, Iain Ward, et al.. (2024). What is the association of preoperative biopsy with recurrence and survival in retroperitoneal sarcoma? A systematic review by the Australia and New Zealand Sarcoma Association clinical practice guidelines working party. Critical Reviews in Oncology/Hematology. 197. 104354–104354. 2 indexed citations
3.
Long, Georgina V., Matteo S. Carlino, George Au‐Yeung, et al.. (2024). Neoadjuvant pembrolizumab, dabrafenib and trametinib in BRAFV600-mutant resectable melanoma: the randomized phase 2 NeoTrio trial. Nature Medicine. 30(9). 2540–2548. 15 indexed citations
4.
Zhou, Li, Edward Hsiao, Serigne Lo, et al.. (2024). FDG-PET associations with pathological response and survival with neoadjuvant immunotherapy for melanoma.. Journal of Clinical Oncology. 42(16_suppl). 9523–9523.
5.
Rafiq, Meena, Jasper de Boer, Jayesh Desai, et al.. (2024). Clinical activity in general practice before sarcoma diagnosis: an Australian cohort study. British Journal of General Practice. 74(745). e508–e516. 2 indexed citations
10.
Mills, Jane K., Melissa A. Henderson, Lauren Giuffrida, et al.. (2021). Generating CAR T cells from tumor-infiltrating lymphocytes. SHILAP Revista de lepidopterología. 9. 955837343–955837343. 11 indexed citations
11.
Hughes, Michael, Gabrielle Williams, David Gyorki, et al.. (2021). Desmoplastic melanoma: a review of its pathology and clinical behaviour, and of management recommendations in published guidelines. Journal of the European Academy of Dermatology and Venereology. 35(6). 1290–1298. 13 indexed citations
12.
Rapport, Frances, Andrea L. Smith, Anne Ε. Cust, et al.. (2020). Identifying challenges to implementation of clinical practice guidelines for sentinel lymph node biopsy in patients with melanoma in Australia: protocol paper for a mixed methods study. BMJ Open. 10(2). e032636–e032636. 3 indexed citations
13.
Lisy, Karolina, Julia Lai‐Kwon, Andrew C. Ward, et al.. (2020). Patient-reported outcomes in melanoma survivors at 1, 3 and 5 years post-diagnosis: a population-based cross-sectional study. Quality of Life Research. 29(8). 2021–2027. 11 indexed citations
14.
Hochheiser, Katharina, Han Xian Aw Yeang, Teagan Wagner, et al.. (2019). Accumulation of CD103+ CD8+ T cells in a cutaneous melanoma micrometastasis. Clinical & Translational Immunology. 8(12). e1100–e1100. 8 indexed citations
15.
Halse, Heloise M., Andrew J. Colebatch, Pasquale Petrone, et al.. (2018). Multiplex immunohistochemistry accurately defines the immune context of metastatic melanoma. Scientific Reports. 8(1). 11158–11158. 74 indexed citations
16.
Beavis, Paul A., Melissa A. Henderson, Lauren Giuffrida, et al.. (2017). Targeting the adenosine 2A receptor enhances chimeric antigen receptor T cell efficacy. Journal of Clinical Investigation. 127(3). 929–941. 259 indexed citations
17.
Boyle, Samantha E., Clare G. Fedele, Vincent Corbin, et al.. (2016). CD271 Expression on Patient Melanoma Cells Is Unstable and Unlinked to Tumorigenicity. Cancer Research. 76(13). 3965–3977. 24 indexed citations
18.
19.
Gyorki, David, Brian R. Untch, R. Michael Tuttle, & Ashok R. Shaha. (2013). Prophylactic Central Neck Dissection in Differentiated Thyroid Cancer: An Assessment of the Evidence. Annals of Surgical Oncology. 20(7). 2285–2289. 51 indexed citations
20.
Hawkins, William G., Klaus J. Busam, Leah Ben‐Porat, et al.. (2005). Desmoplastic Melanoma: A Pathologically and Clinically Distinct Form of Cutaneous Melanoma. Annals of Surgical Oncology. 12(3). 207–213. 110 indexed citations

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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