Daniel Lee

13.1k total citations · 2 hit papers
271 papers, 8.2k citations indexed

About

Daniel Lee is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Daniel Lee has authored 271 papers receiving a total of 8.2k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Radiology, Nuclear Medicine and Imaging, 88 papers in Cardiology and Cardiovascular Medicine and 49 papers in Surgery. Recurrent topics in Daniel Lee's work include Cardiac Imaging and Diagnostics (79 papers), Advanced MRI Techniques and Applications (54 papers) and Cardiovascular Function and Risk Factors (35 papers). Daniel Lee is often cited by papers focused on Cardiac Imaging and Diagnostics (79 papers), Advanced MRI Techniques and Applications (54 papers) and Cardiovascular Function and Risk Factors (35 papers). Daniel Lee collaborates with scholars based in United States, United Kingdom and Canada. Daniel Lee's co-authors include Albert Bendelac, Se‐Ho Park, Edwin Wu, Andrew J. Beavis, Yasuhiko Koezuka, Claude Carnaud, James Carr, Aizhi Zhu, Hyunsuk Shim and Jose T. Ortiz‐Pérez and has published in prestigious journals such as JAMA, Journal of Biological Chemistry and Circulation.

In The Last Decade

Daniel Lee

258 papers receiving 8.1k citations

Hit Papers

Cutting Edge: Cross-Talk Between Cells of the Innate Immu... 1999 2026 2008 2017 1999 2013 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Lee United States 43 2.5k 2.0k 1.9k 1.1k 1.1k 271 8.2k
Koïchi Shimizu Japan 50 592 0.2× 1.5k 0.8× 2.3k 1.2× 2.0k 1.8× 1.7k 1.6× 338 8.5k
Marcus Y. Chen United States 44 2.2k 0.9× 2.6k 1.3× 733 0.4× 595 0.5× 1.3k 1.2× 273 7.2k
Drew A. Torigian United States 46 528 0.2× 2.1k 1.1× 2.3k 1.2× 1.0k 1.0× 1.5k 1.4× 323 9.4k
Dong‐Ho Shin South Korea 43 2.5k 1.0× 2.6k 1.3× 713 0.4× 681 0.6× 3.2k 2.9× 343 8.2k
Christoph Pohl Germany 44 590 0.2× 1.1k 0.6× 1.3k 0.7× 721 0.7× 453 0.4× 170 6.9k
Nancy L. Geller United States 61 2.1k 0.8× 1.1k 0.6× 634 0.3× 1.4k 1.3× 4.9k 4.5× 220 11.5k
Michael Kasper Germany 51 1.1k 0.4× 709 0.4× 977 0.5× 3.6k 3.3× 1.2k 1.1× 249 10.7k
Ferdinand C. Breedveld Netherlands 67 824 0.3× 3.4k 1.8× 5.4k 2.9× 2.3k 2.1× 1.2k 1.1× 182 21.9k
Norbert Frey Germany 49 5.2k 2.1× 596 0.3× 891 0.5× 6.4k 5.8× 1.4k 1.3× 500 11.9k
James H.F. Rudd United Kingdom 54 3.7k 1.5× 5.0k 2.6× 1.6k 0.9× 1.1k 1.0× 2.5k 2.3× 174 11.0k

Countries citing papers authored by Daniel Lee

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Lee. A scholar is included among the top collaborators of Daniel Lee 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 Daniel Lee. Daniel Lee 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.
Sun, Yin, Abraham Bayer, Daniel Lee, et al.. (2025). Novel Therapeutic Approach Targeting CXCR3 to Treat Immunotherapy Myocarditis. Circulation Research. 136(5). 473–490. 3 indexed citations
2.
Catania, Roberta, Amir Ali Rahsepar, Kelvin Chow, et al.. (2025). Quantitative Stress First-Pass Perfusion Cardiac MRI: State of the Art. Radiographics. 45(3). e240115–e240115. 4 indexed citations
3.
Tavakoli, Neda, Amir Ali Rahsepar, Brandon Benefield, et al.. (2025). ScarNet: a novel foundation model for automated myocardial scar quantification from late gadolinium-enhancement images. Journal of Cardiovascular Magnetic Resonance. 27(2). 101945–101945. 1 indexed citations
4.
Sukul, Devraj, Milan Seth, Ryan D. Madder, et al.. (2024). Contemporary Trends and Outcomes of Intravascular Lithotripsy in Percutaneous Coronary Intervention. JACC: Cardiovascular Interventions. 17(15). 1811–1821. 6 indexed citations
5.
Pradeep, Ronak, Daniel Lee, Ali Mousavi, et al.. (2024). ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA Datasets with Large Language Models. 1176–1206. 3 indexed citations
6.
Allen, Bradley D., James Carr, Rod Passman, et al.. (2024). Ultra-rapid, Free-breathing, Real-time Cardiac Cine MRI Using GRASP Amplified with View Sharing and KWIC Filtering. Radiology Cardiothoracic Imaging. 6(1). e230107–e230107. 3 indexed citations
7.
Zhu, Han, Francisco X. Galdos, Daniel Lee, et al.. (2022). Identification of Pathogenic Immune Cell Subsets Associated With Checkpoint Inhibitor–Induced Myocarditis. Circulation. 146(4). 316–335. 103 indexed citations
8.
Popescu, Dan M., Julie K. Shade, Konstantinos N. Aronis, et al.. (2022). Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart. Nature Cardiovascular Research. 1(4). 334–343. 58 indexed citations
10.
Radomska, Anna, et al.. (2021). A retrospective study on incidence, diagnosis, and clinical outcome of gastric-type endocervical adenocarcinoma in a single institution. Diagnostic Pathology. 16(1). 68–68. 5 indexed citations
12.
Veluw, Susanne J. van, Matthew P. Frosch, Ashley A. Scherlek, et al.. (2020). In vivo characterization of spontaneous microhemorrhage formation in mice with cerebral amyloid angiopathy. Journal of Cerebral Blood Flow & Metabolism. 41(1). 82–91. 20 indexed citations
13.
Allen, Bradley D., et al.. (2020). Highly Accelerated Real-Time Free-Breathing Cine CMR for Patients With a Cardiac Implantable Electronic Device. Academic Radiology. 28(12). 1779–1786. 3 indexed citations
14.
Zhou, Xin, Dong Ren, Shan Zeng, et al.. (2016). The Kinetics of Circulating Monocyte Subsets and Monocyte-Platelet Aggregates in the Acute Phase of ST-Elevation Myocardial Infarction. Medicine. 95(18). e3466–e3466. 41 indexed citations
15.
Shah, Sanjiv J., Michael J. Cuttica, Lauren Beussink‐Nelson, et al.. (2012). Abstract 18974: A Pilot Study of the Effects of Ranolazine on Right Ventricular Structure and Function, Exercise Capacity, and Symptoms in Pulmonary Arterial Hypertension. Circulation. 126(suppl_21). 1 indexed citations
16.
Lee, Daniel, et al.. (2011). Effect of Hyponatremia in Isolated Rat Hearts. The FASEB Journal. 25. 1 indexed citations
17.
Lee, Daniel. (2005). Buffalo Hump Is Associated with Hyperinsulinemia and Dyslipidemia in HIV Patients with Excess Visceral Adipose Tissue (VAT). 1 indexed citations
18.
Hellerstein, Marc K., Rebecca Hoh, Mary Beth Hanley, et al.. (2003). Subpopulations of long-lived and short-lived T cells in advanced HIV-1 infection. Journal of Clinical Investigation. 112(6). 956–966. 163 indexed citations
19.
Shin, Jitae, Daniel Lee, & C.‐C. Jay Kuo. (2003). Quality of service for internet multimedia. CERN Document Server (European Organization for Nuclear Research). 11 indexed citations
20.
Howatson, A.F., et al.. (1992). NSAIDs pathology and therapy. Gut. 33(1 Suppl). S5–S5. 2 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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