Luke Yoon

779 total citations
23 papers, 550 citations indexed

About

Luke Yoon is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Luke Yoon has authored 23 papers receiving a total of 550 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Pulmonary and Respiratory Medicine and 7 papers in Molecular Biology. Recurrent topics in Luke Yoon's work include Renal cell carcinoma treatment (7 papers), MRI in cancer diagnosis (6 papers) and Hepatocellular Carcinoma Treatment and Prognosis (5 papers). Luke Yoon is often cited by papers focused on Renal cell carcinoma treatment (7 papers), MRI in cancer diagnosis (6 papers) and Hepatocellular Carcinoma Treatment and Prognosis (5 papers). Luke Yoon collaborates with scholars based in United States, Taiwan and Italy. Luke Yoon's co-authors include William E. Palmer, Ara Kassarjian, Michael B. Millis, Étienne L. Belzile, Susan A. Connolly, Justin R. Tse, Aya Kamaya, Jody Shen, Luyao Shen and James A. Brink and has published in prestigious journals such as Molecular and Cellular Biology, Radiology and The Journal of Urology.

In The Last Decade

Luke Yoon

21 papers receiving 536 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luke Yoon United States 9 310 123 106 104 81 23 550
Eric Weinberg United States 11 331 1.1× 137 1.1× 202 1.9× 22 0.2× 117 1.4× 26 687
Hideo Onitsuka Japan 13 225 0.7× 69 0.6× 234 2.2× 52 0.5× 115 1.4× 19 523
Roberto Caudana Italy 13 213 0.7× 130 1.1× 94 0.9× 31 0.3× 51 0.6× 35 516
Ali Seif Amir Hosseini Germany 12 286 0.9× 119 1.0× 164 1.5× 78 0.8× 23 0.3× 55 494
Emin Yener Gültekin Türkiye 13 202 0.7× 86 0.7× 163 1.5× 114 1.1× 54 0.7× 37 490
D. Brkovic Germany 9 127 0.4× 36 0.3× 233 2.2× 115 1.1× 35 0.4× 29 385
Daria Motamedi United States 14 243 0.8× 37 0.3× 177 1.7× 32 0.3× 238 2.9× 35 519
M.S. Michel Germany 12 156 0.5× 41 0.3× 297 2.8× 71 0.7× 54 0.7× 47 514
Şebnem Örgüç Türkiye 11 238 0.8× 79 0.6× 75 0.7× 18 0.2× 86 1.1× 43 485
Jordy P. Pijl Netherlands 9 109 0.4× 97 0.8× 68 0.6× 17 0.2× 18 0.2× 11 295

Countries citing papers authored by Luke Yoon

Since Specialization
Citations

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

Fields of papers citing papers by Luke Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luke Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Luke Yoon. A scholar is included among the top collaborators of Luke Yoon 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 Luke Yoon. Luke Yoon 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.
2.
Beaulieu, Christopher F., et al.. (2024). Deep Learning for Automated Classification of Hip Hardware on Radiographs. Journal of Imaging Informatics in Medicine. 38(2). 988–996. 1 indexed citations
3.
Shen, Luyao, Luke Yoon, Patrick Mullane, Tie Liang, & Justin R. Tse. (2024). World Health Organization 2022 Classification Update: Radiologic and Pathologic Features of Papillary Renal Cell Carcinomas. Academic Radiology. 31(8). 3257–3265. 3 indexed citations
4.
5.
Yoon, Luke, Terry S. Desser, Clinton Jokerst, et al.. (2024). Top down and bottom up: A review of strategies for wellness programs in academic radiology. Clinical Imaging. 109. 110131–110131. 1 indexed citations
6.
Yoon, Luke, et al.. (2024). Diagnostic performance of CT/MRI LI-RADS v2018 in non-cirrhotic steatotic liver disease. European Radiology. 34(12). 7622–7631. 3 indexed citations
7.
Shen, Luyao, Justin R. Tse, Luke Yoon, et al.. (2023). Risk of malignancy in T1-hyperintense Bosniak version 2019 class II and IIF cystic renal masses. Abdominal Radiology. 48(8). 2636–2648. 2 indexed citations
8.
Tse, Justin R., Luyao Shen, Jody Shen, Luke Yoon, & Aya Kamaya. (2022). Nyquist sampling theorem and Bosniak classification, version 2019: effect of thin axial sections on categorization and agreement. European Radiology. 32(12). 8256–8265. 1 indexed citations
9.
Tse, Justin R., Luyao Shen, Thodsawit Tiyarattanachai, et al.. (2022). Positive predictive value of LI-RADS US-3 observations: multivariable analysis of clinical and imaging features. Abdominal Radiology. 48(1). 271–281. 8 indexed citations
10.
Shen, Luyao, et al.. (2022). Diagnostic performance of hypoechoic perinephric fat as a predictor of prediabetes and diabetes. Abdominal Radiology. 48(2). 669–679. 3 indexed citations
11.
Shen, Luyao, Luke Yoon, Benjamin I. Chung, Aya Kamaya, & Justin R. Tse. (2022). Outcomes of Bosniak Classification Version 2019 Class IIF Cystic Renal Masses at Imaging Surveillance. American Journal of Roentgenology. 220(5). 705–717. 8 indexed citations
12.
Tse, Justin R., et al.. (2022). Outcomes of LI-RADS US-2 Subthreshold Observations Detected on Surveillance Ultrasound. American Journal of Roentgenology. 219(5). 774–783. 6 indexed citations
13.
Yoon, Luke, et al.. (2021). S1R PET/MRI of patients with chronic knee pain reveals potential pain generators not otherwise identified with standard care: Early experience.. 62. 143–143. 1 indexed citations
14.
Tse, Justin R., Luyao Shen, Jody Shen, Luke Yoon, & Aya Kamaya. (2020). Prevalence of Malignancy and Histopathological Association of Bosniak Classification, Version 2019 Class III and IV Cystic Renal Masses. The Journal of Urology. 205(4). 1031–1038. 21 indexed citations
15.
Lasco, Todd, et al.. (2016). Disseminated coccidioidomycosis with multifocal musculoskeletal disease involvement. Radiology Case Reports. 12(1). 141–145. 10 indexed citations
16.
Yoon, Luke, Onofrio A. Catalano, Stefan Fritz, et al.. (2009). Another Dimension in Magnetic Resonance Cholangiopancreatography. Journal of Computer Assisted Tomography. 33(3). 363–368. 38 indexed citations
17.
Yoon, Luke, William E. Palmer, & Ara Kassarjian. (2007). Evaluation of radial-sequence imaging in detecting acetabular labral tears at hip MR arthrography. Skeletal Radiology. 36(11). 1029–1033. 41 indexed citations
18.
Kassarjian, Ara, Luke Yoon, Étienne L. Belzile, et al.. (2005). Triad of MR Arthrographic Findings in Patients with Cam-Type Femoroacetabular Impingement. Radiology. 236(2). 588–592. 232 indexed citations
19.
Yoon, Luke, Andrew Haims, James A. Brink, Reuven Rabinovici, & Howard P. Forman. (2002). Evaluation of an Emergency Radiology Quality Assurance Program at a Level I Trauma Center: Abdominal and Pelvic CT Studies. Radiology. 224(1). 42–46. 55 indexed citations
20.
Weissinger, Eva M., Günther Eißner, Burkhard Haefner, et al.. (1997). Inhibition of the Raf-1 Kinase by Cyclic AMP Agonists Causes Apoptosis of v-abl-Transformed Cells. Molecular and Cellular Biology. 17(6). 3229–3241. 60 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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