Raul N. Uppot

4.0k total citations
107 papers, 2.6k citations indexed

About

Raul N. Uppot is a scholar working on Surgery, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Raul N. Uppot has authored 107 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Surgery, 39 papers in Pulmonary and Respiratory Medicine and 30 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Raul N. Uppot's work include Renal cell carcinoma treatment (20 papers), Hepatocellular Carcinoma Treatment and Prognosis (11 papers) and Renal and related cancers (10 papers). Raul N. Uppot is often cited by papers focused on Renal cell carcinoma treatment (20 papers), Hepatocellular Carcinoma Treatment and Prognosis (11 papers) and Renal and related cancers (10 papers). Raul N. Uppot collaborates with scholars based in United States, Taiwan and China. Raul N. Uppot's co-authors include Peter F. Hahn, Ronald S. Arellano, Peter R. Müeller, Dushyant V. Sahani, Debra A. Gervais, Dushyant V. Sahani, Debra A. Gervais, Colin J. McCarthy, Brian H. Eisner and Cristina R. Ferrone and has published in prestigious journals such as New England Journal of Medicine, PLoS ONE and Radiology.

In The Last Decade

Raul N. Uppot

101 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Raul N. Uppot United States 27 898 896 729 475 397 107 2.6k
F. Cornélis France 34 1.5k 1.7× 809 0.9× 960 1.3× 482 1.0× 378 1.0× 214 3.6k
Timothy J. Ziemlewicz United States 33 856 1.0× 806 0.9× 756 1.0× 898 1.9× 752 1.9× 112 3.1k
Seung Eun Jung South Korea 31 662 0.7× 1.1k 1.2× 714 1.0× 391 0.8× 253 0.6× 164 3.6k
Laure Fournier France 30 961 1.1× 598 0.7× 1.4k 1.9× 433 0.9× 169 0.4× 136 3.5k
Kedar N. Chintapalli United States 23 793 0.9× 905 1.0× 375 0.5× 200 0.4× 529 1.3× 64 2.1k
Andrew D. Smith United States 28 1.3k 1.4× 445 0.5× 1.5k 2.1× 391 0.8× 388 1.0× 117 3.2k
Gianpaolo Carrafiello Italy 33 1.3k 1.5× 1.4k 1.6× 779 1.1× 414 0.9× 799 2.0× 236 3.8k
Anna Maria Ierardi Italy 29 1.1k 1.3× 1.1k 1.2× 510 0.7× 335 0.7× 510 1.3× 242 2.8k
Susan C. Charman United Kingdom 33 1.8k 2.0× 1.1k 1.2× 364 0.5× 195 0.4× 202 0.5× 95 3.3k
Ronald S. Arellano United States 33 2.2k 2.5× 1.4k 1.5× 915 1.3× 439 0.9× 740 1.9× 150 4.0k

Countries citing papers authored by Raul N. Uppot

Since Specialization
Citations

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

Fields of papers citing papers by Raul N. Uppot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raul N. Uppot

This figure shows the co-authorship network connecting the top 25 collaborators of Raul N. Uppot. A scholar is included among the top collaborators of Raul N. Uppot 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 Raul N. Uppot. Raul N. Uppot 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
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Yun, Jung H., Arian Mansur, C. Newton, et al.. (2025). The growing armamentarium of image-guided tumor ablation in interventional oncology. PubMed. 2(5). umaf033–umaf033. 1 indexed citations
3.
Fintelmann, Florian J., et al.. (2024). Limited Effectiveness in Early Human Clinical Experience with Pulsed Electrical Field Ablation. Journal of Vascular and Interventional Radiology. 36(2). 274–281. 4 indexed citations
4.
Lang, Min, et al.. (2024). Medical Extended Reality for Radiology Education and Training. Journal of the American College of Radiology. 21(10). 1583–1594. 9 indexed citations
5.
Capua, John Di, Dufan Wu, Sanjeeva P. Kalva, et al.. (2024). Transient, Image‐Guided Gel‐Dissection for Percutaneous Thermal Ablation. Advanced Healthcare Materials. 14(28). e2400272–e2400272. 2 indexed citations
6.
7.
Daye, Dania, et al.. (2021). Role of Machine Learning and Artificial Intelligence in Interventional Oncology. Current Oncology Reports. 23(6). 70–70. 18 indexed citations
8.
Wu, Jonathan, Lipika Goyal, Ryan David Nipp, et al.. (2018). The Tipping Point: Key Oncologic Imaging Findings Resulting in Critical Changes in the Management of Malignant Tumors of the Gastrointestinal Tract. Current Problems in Diagnostic Radiology. 48(1). 61–74. 1 indexed citations
9.
McCarthy, Colin J., Aoife Kilcoyne, Xinhua Li, et al.. (2018). Radiation Dose and Risk Estimates of CT-Guided Percutaneous Liver Ablations and Factors Associated with Dose Reduction. CardioVascular and Interventional Radiology. 41(12). 1935–1942. 5 indexed citations
10.
Prabhakar, Anand M., et al.. (2017). Adapting a Computerized Medical Dictation System to Prepare Academic Papers in Radiology. Current Problems in Diagnostic Radiology. 47(6). 393–396. 1 indexed citations
11.
Uppot, Raul N., Colin J. McCarthy, Alex B. Haynes, et al.. (2017). A Verbal Electronic Checklist for Timeouts Linked to the Electronic Health Record. Journal of the American College of Radiology. 14(10). 1322–1325. 3 indexed citations
12.
Asvadi, Nazanin H., Arash Anvari, Raul N. Uppot, et al.. (2016). CT-Guided Percutaneous Microwave Ablation of Tumors in the Hepatic Dome: Assessment of Efficacy and Safety. Journal of Vascular and Interventional Radiology. 27(4). 496–502. 39 indexed citations
13.
Butros, Selim R., et al.. (2014). Image-Guided Percutaneous Thermal Ablation of Metastatic Pelvic Tumor From Gynecologic Malignancies. Obstetrics and Gynecology. 123(3). 500–505. 9 indexed citations
14.
Gervais, Debra A., Michael A. Blake, Peter R. Müeller, et al.. (2013). Imaging-Guided Biopsy of 18F-FDG–Avid Extrapulmonary Lesions: Do Lesion Location and Morphologic Features on CT Affect the Positive Predictive Value for Malignancy?. American Journal of Roentgenology. 201(2). 433–438. 11 indexed citations
15.
Uppot, Raul N., Mukesh G. Harisinghani, & Debra A. Gervais. (2010). Imaging-Guided Percutaneous Renal Biopsy: Rationale and Approach. American Journal of Roentgenology. 194(6). 1443–1449. 62 indexed citations
16.
Miller, Janet C., William E. Palmer, Allan H. Goroll, James H. Thrall, & Raul N. Uppot. (2009). Anesthetic and Steroid Injections for Musculoskeletal Pain. Journal of the American College of Radiology. 6(11). 806–808. 2 indexed citations
17.
Freedman, Steven D., Raul N. Uppot, & Mari Mino–Kenudson. (2009). Case 26-2009. New England Journal of Medicine. 361(8). 807–816. 6 indexed citations
18.
Uppot, Raul N., Dushyant V. Sahani, Peter F. Hahn, Debra A. Gervais, & Peter R. Müeller. (2007). Impact of Obesity on Medical Imaging and Image-Guided Intervention. American Journal of Roentgenology. 188(2). 433–440. 158 indexed citations
19.
Uppot, Raul N., et al.. (2001). Positron emission tomography (PET) imaging for solitary pulmonary nodules--review of the Delaware experience.. PubMed. 73(10). 381–5. 1 indexed citations
20.
Uppot, Raul N., et al.. (1999). Unusual case of lumbar synovial cyst. Clinical Imaging. 23(6). 394–396. 11 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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