Gopal N. Gupta

15.8k total citations
164 papers, 2.9k citations indexed

About

Gopal N. Gupta is a scholar working on Pulmonary and Respiratory Medicine, Surgery and Molecular Biology. According to data from OpenAlex, Gopal N. Gupta has authored 164 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Pulmonary and Respiratory Medicine, 56 papers in Surgery and 50 papers in Molecular Biology. Recurrent topics in Gopal N. Gupta's work include Renal cell carcinoma treatment (41 papers), Prostate Cancer Diagnosis and Treatment (36 papers) and Renal and related cancers (29 papers). Gopal N. Gupta is often cited by papers focused on Renal cell carcinoma treatment (41 papers), Prostate Cancer Diagnosis and Treatment (36 papers) and Renal and related cancers (29 papers). Gopal N. Gupta collaborates with scholars based in United States, India and United Kingdom. Gopal N. Gupta's co-authors include Paul C. Kuo, Robert H. Blackwell, Kimberly E. Foreman, Carrie A. Franzen, Robert C. Flanigan, W. Marston Linehan, Peter A. Pinto, Anai N. Kothari, Gennady Bratslavsky and Matthew Zapf and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Gopal N. Gupta

156 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gopal N. Gupta United States 29 1.2k 1.2k 705 655 318 164 2.9k
Eu Chang Hwang South Korea 26 598 0.5× 1.3k 1.1× 901 1.3× 317 0.5× 648 2.0× 229 2.8k
Karl Pummer Austria 37 1.0k 0.8× 2.0k 1.7× 1.2k 1.8× 815 1.2× 1.0k 3.3× 156 4.1k
Ricardo Rendon Canada 30 1.3k 1.1× 2.1k 1.8× 1.4k 2.0× 333 0.5× 542 1.7× 193 3.4k
Thomas L. Jang United States 22 979 0.8× 1.4k 1.2× 637 0.9× 221 0.3× 579 1.8× 120 2.5k
Costas D. Lallas United States 30 836 0.7× 1.9k 1.6× 960 1.4× 347 0.5× 788 2.5× 162 3.9k
Edouard J. Trabulsi United States 33 552 0.4× 2.3k 1.9× 1.3k 1.9× 494 0.8× 841 2.6× 201 4.0k
Jacques Irani France 30 490 0.4× 1.5k 1.2× 1.1k 1.6× 337 0.5× 428 1.3× 166 2.8k
Jörg Fuchs Germany 27 660 0.5× 837 0.7× 953 1.4× 222 0.3× 518 1.6× 171 3.0k
Alessandro Larcher Italy 34 901 0.7× 2.9k 2.5× 1.5k 2.1× 371 0.6× 510 1.6× 233 4.1k
Anil Mandhani India 36 1.1k 0.9× 1.2k 1.1× 1.7k 2.4× 401 0.6× 424 1.3× 184 4.0k

Countries citing papers authored by Gopal N. Gupta

Since Specialization
Citations

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

Fields of papers citing papers by Gopal N. Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gopal N. Gupta. 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 Gopal N. Gupta. The network helps show where Gopal N. Gupta may publish in the future.

Co-authorship network of co-authors of Gopal N. Gupta

This figure shows the co-authorship network connecting the top 25 collaborators of Gopal N. Gupta. A scholar is included among the top collaborators of Gopal N. Gupta 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 Gopal N. Gupta. Gopal N. Gupta 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.
Bova, Davide, et al.. (2025). Peak early‐phase enhancement ratio on contrast‐enhanced MRI to differentiate chromophobe renal cell carcinoma from oncocytoma. BJUI Compass. 6(4). e70017–e70017. 1 indexed citations
2.
Gupta, Veena, et al.. (2024). 5P Using AI and clinical knowledge to find missed lung and ovarian cancer patients. ESMO Open. 9. 102382–102382. 1 indexed citations
3.
Patel, Hiten D., Sebastiaan Remmers, Eric V. Li, et al.. (2024). Comparison of Magnetic Resonance Imaging–Based Risk Calculators to Predict Prostate Cancer Risk. JAMA Network Open. 7(3). e241516–e241516. 8 indexed citations
4.
Giridhar, Prashanth, Alec M. Block, James S. Welsh, et al.. (2024). A Systematic Review of Clinical Trials Comparing Radiation Therapy Versus Radical Prostatectomy in Prostate Cancer. Clinical Genitourinary Cancer. 22(5). 102157–102157. 1 indexed citations
5.
Patel, Hiten D., Christopher James, Ceressa T. Ward, et al.. (2023). Urinary comprehensive genomic profiling predicts urothelial carcinoma recurrence and identifies responders to intravesical therapy. Molecular Oncology. 18(2). 291–304. 3 indexed citations
6.
Patel, Hiten D., Whitney Halgrimson, Steven M. Shea, et al.. (2023). Variability in prostate cancer detection among radiologists and urologists using MRI fusion biopsy. SHILAP Revista de lepidopterología. 5(2). 304–312. 3 indexed citations
7.
Srivastava, Arnav, Hiren V. Patel, Gopal N. Gupta, et al.. (2022). Survival of nonseminomatous germ cell tumors in pediatric patients and young adults – A stage group stratified analysis. Urologic Oncology Seminars and Original Investigations. 40(4). 169.e1–169.e12. 2 indexed citations
8.
9.
Patel, Hiten D., et al.. (2022). Robotic-assisted tumor enucleation versus standard margin partial nephrectomy: Perioperative, renal functional, and oncologic outcomes for low and intermediate complexity renal masses. Urologic Oncology Seminars and Original Investigations. 40(7). 347.e9–347.e16. 13 indexed citations
10.
Fang, Andrew M., Kimberly D. Martin, Richard E. Fan, et al.. (2022). Multi‐institutional analysis of clinical and imaging risk factors for detecting clinically significant prostate cancer in men with PI‐RADS 3 lesions. Cancer. 128(18). 3287–3296. 21 indexed citations
11.
Patel, Hiten D., Robert C. Flanigan, Alex Gorbonos, et al.. (2022). Percentage of sarcomatoid histology is associated with survival in renal cell carcinoma: Stratification and implications by clinical metastatic stage. Urologic Oncology Seminars and Original Investigations. 40(7). 347.e1–347.e8. 4 indexed citations
12.
13.
Flack, Chandra K., Adam Calaway, Maria M. Picken, et al.. (2019). Comparing oncologic outcomes in patients undergoing surgery for oncocytic neoplasms, conventional oncocytoma, and chromophobe renal cell carcinoma. Urologic Oncology Seminars and Original Investigations. 37(11). 811.e17–811.e21. 5 indexed citations
14.
Bajic, Petar, Alan J. Wolfe, & Gopal N. Gupta. (2019). The Urinary Microbiome: Implications in Bladder Cancer Pathogenesis and Therapeutics. Urology. 126. 10–15. 62 indexed citations
15.
Kirshenbaum, Eric, Robert H. Blackwell, William S. Gange, et al.. (2018). Thirty-day hospital revisits after prostate brachytherapy: who is at risk?. Prostate International. 7(2). 68–72. 2 indexed citations
16.
Blackwell, Robert H., Carrie A. Franzen, & Gopal N. Gupta. (2017). Exosomes: an evolving source of urinary biomarkers and an up-and-coming therapeutic delivery vehicle. Translational Cancer Research. 6(1). 1 indexed citations
17.
18.
Greco, Kristin A., Carrie A. Franzen, Kimberly E. Foreman, et al.. (2016). PLK-1 Silencing in Bladder Cancer by siRNA Delivered With Exosomes. Urology. 91. 241.e1–241.e7. 138 indexed citations
19.
Blackwell, Robert H., Zachary Kozel, Zhiling Zhang, et al.. (2016). Functional Implications of Renal Tumor Enucleation Relative to Standard Partial Nephrectomy. Urology. 99. 162–168. 29 indexed citations
20.
Sourbier, Carole, Manik C. Ghosh, Youfeng Yang, et al.. (2012). Targeting HIF2α Translation with Tempol in VHL-Deficient Clear Cell Renal Cell Carcinoma. Oncotarget. 3(11). 1472–1482. 19 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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