Udo Hoffmann

47.6k total citations · 12 hit papers
555 papers, 31.3k citations indexed

About

Udo Hoffmann is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Udo Hoffmann has authored 555 papers receiving a total of 31.3k indexed citations (citations by other indexed papers that have themselves been cited), including 392 papers in Radiology, Nuclear Medicine and Imaging, 306 papers in Cardiology and Cardiovascular Medicine and 148 papers in Surgery. Recurrent topics in Udo Hoffmann's work include Cardiac Imaging and Diagnostics (371 papers), Advanced X-ray and CT Imaging (104 papers) and Acute Myocardial Infarction Research (103 papers). Udo Hoffmann is often cited by papers focused on Cardiac Imaging and Diagnostics (371 papers), Advanced X-ray and CT Imaging (104 papers) and Acute Myocardial Infarction Research (103 papers). Udo Hoffmann collaborates with scholars based in United States, Germany and Austria. Udo Hoffmann's co-authors include Joseph M. Massaro, Caroline S. Fox, Maros Ferencik, Thomas J. Brady, Christopher J. O’Donnell, Ricardo C. Cury, Suhny Abbara, Ramachandran S. Vasan, Stephan Achenbach and Quynh A. Truong and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and The Lancet.

In The Last Decade

Udo Hoffmann

545 papers receiving 30.5k citations

Hit Papers

Artificial intelligence i... 2003 2026 2010 2018 2019 2015 2008 2009 2003 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Artificial intelligence in cancer imaging: Clinical challenges and applications
    2019 1.2k citations Raymond H. Mak, Udo Hoffmann et al. profile →
  2. Outcomes of Anatomical versus Functional Testing for Coronary Artery Disease
    2015 846 citations Pamela S. Douglas, Udo Hoffmann et al. profile →
  3. Pericardial Fat, Visceral Abdominal Fat, Cardiovascular Disease Risk Factors, and Vascular Calcification in a Community-Based Sample
    2008 831 citations Guido Aranha Rosito, Joseph M. Massaro et al. Circulation profile →
  4. Fibroblast Growth Factor 23 and Left Ventricular Hypertrophy in Chronic Kidney Disease
    2009 659 citations Orlando M. Gutiérrez, James L. Januzzi et al. Circulation profile →
  5. Detection of Calcified and Noncalcified Coronary Atherosclerotic Plaque by Contrast-Enhanced, Submillimeter Multidetector Spiral Computed Tomography
    2003 617 citations Maros Ferencik, Udo Hoffmann et al. Circulation profile →
  6. Body Fat Distribution, Incident Cardiovascular Disease, Cancer, and All-Cause Mortality
    2013 511 citations Joseph M. Massaro, Udo Hoffmann et al. profile →
  7. Relation between resting amygdalar activity and cardiovascular events: a longitudinal and cohort study
    2017 420 citations Ahmed Tawakol, Amparo L. Figueroa et al. profile →
  8. High-Risk Plaque Detected on Coronary CT Angiography Predicts Acute Coronary Syndromes Independent of Significant Stenosis in Acute Chest Pain
    2014 362 citations Stefan B. Puchner, Ting Liu et al. profile →
  9. Association Between Immune Checkpoint Inhibitors With Cardiovascular Events and Atherosclerotic Plaque
    2020 356 citations Jana Taron, Vineet K. Raghu et al. Circulation profile →
  10. Arterial Inflammation in Patients With HIV
    2012 352 citations Sharath Subramanian, Ahmed Tawakol et al. profile →
  11. Use of High-Risk Coronary Atherosclerotic Plaque Detection for Risk Stratification of Patients With Stable Chest Pain
    2018 328 citations Maros Ferencik, Thomas Mayrhofer et al. profile →
  12. Prognostic Value of Noninvasive Cardiovascular Testing in Patients With Stable Chest Pain
    2017 273 citations Udo Hoffmann, Maros Ferencik et al. Circulation profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Udo Hoffmann 16.4k 14.0k 8.8k 5.5k 4.1k 555 31.3k
J. Jeffrey Carr 8.1k 0.5× 11.0k 0.8× 5.3k 0.6× 2.4k 0.4× 3.5k 0.9× 473 25.0k
Leslee J. Shaw 26.9k 1.6× 23.8k 1.7× 12.4k 1.4× 7.0k 1.3× 3.7k 0.9× 634 41.7k
Ron Blankstein 10.4k 0.6× 10.8k 0.8× 5.9k 0.7× 2.9k 0.5× 2.8k 0.7× 530 21.5k
João A.C. Lima 23.3k 1.4× 35.5k 2.5× 9.3k 1.1× 5.3k 1.0× 6.6k 1.6× 1.0k 53.8k
Thomas H. Marwick 21.0k 1.3× 41.5k 3.0× 8.2k 0.9× 3.0k 0.6× 4.8k 1.2× 946 50.1k
Pamela S. Douglas 12.3k 0.7× 26.2k 1.9× 7.9k 0.9× 3.0k 0.6× 4.9k 1.2× 677 39.2k
Raymond J. Gibbons 12.3k 0.7× 22.6k 1.6× 9.3k 1.1× 2.6k 0.5× 2.5k 0.6× 343 33.9k
Jagat Narula 10.3k 0.6× 14.7k 1.0× 8.6k 1.0× 3.0k 0.6× 4.4k 1.1× 547 29.1k
Robert Detrano 12.0k 0.7× 10.9k 0.8× 5.5k 0.6× 3.1k 0.6× 3.2k 0.8× 160 23.3k
Gerhard Schüler 7.7k 0.5× 25.5k 1.8× 12.3k 1.4× 4.1k 0.7× 5.6k 1.4× 652 40.9k

Countries citing papers authored by Udo Hoffmann

Since Specialization
Citations

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

Fields of papers citing papers by Udo Hoffmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Udo Hoffmann

This figure shows the co-authorship network connecting the top 25 collaborators of Udo Hoffmann. A scholar is included among the top collaborators of Udo Hoffmann 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 Udo Hoffmann. Udo Hoffmann 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.
Nurmohamed, Nick S., Jason H. Cole, Matthew J. Budoff, et al.. (2024). Impact of atherosclerosis imaging-quantitative computed tomography on diagnostic certainty, downstream testing, coronary revascularization, and medical therapy: the CERTAIN study. European Heart Journal - Cardiovascular Imaging. 25(6). 857–866. 15 indexed citations
2.
Kolossváry, Márton, Vineet K. Raghu, John Tobias Nagurney, Udo Hoffmann, & Michael T. Lu. (2023). Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome. Radiology. 306(2). e221926–e221926. 8 indexed citations
3.
Giamberardino, Stephanie N., Neha J. Pagidipati, Deepak Voora, et al.. (2023). Branched‐Chain Amino Acids in Computed Tomography–Defined Adipose Depots and Coronary Artery Disease: A PROMISE Trial Biomarker Substudy. Journal of the American Heart Association. 12(11). e028410–e028410. 6 indexed citations
4.
McGarrah, Robert W., Maros Ferencik, Stephanie N. Giamberardino, et al.. (2022). Lipoprotein Subclasses Associated With High‐Risk Coronary Atherosclerotic Plaque: Insights From the PROMISE Clinical Trial. Journal of the American Heart Association. 12(1). e026662–e026662. 5 indexed citations
5.
Takigami, A., Vikas Thondapu, Reece Goiffon, et al.. (2021). Coronary Artery Disease Reporting and Data System (CAD-RADS) Adoption: Analysis of Local Trends in a Large Academic Medical Center. Radiology Cardiothoracic Imaging. 3(3). e210016–e210016. 1 indexed citations
6.
Nayor, Matthew, Li Shen, Gary M. Hunninghake, et al.. (2021). Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop. Circulation Cardiovascular Imaging. 14(8). e012943–e012943. 3 indexed citations
7.
Zeleznik, Roman, Jana Taron, Cindy Hancox, et al.. (2020). Deep Learning Based Heart Segmentation Algorithm to Improve Radiation Treatment Planning. International Journal of Radiation Oncology*Biology*Physics. 108(3). S118–S118.
8.
Eslami, Parastou, Chintan Parmar, Borek Foldyna, et al.. (2020). Radiomics of Coronary Artery Calcium in the Framingham Heart Study. Radiology Cardiothoracic Imaging. 2(1). e190119–e190119. 25 indexed citations
9.
Atkins, Katelyn M., Roman Zeleznik, Tafadzwa L. Chaunzwa, et al.. (2019). Elevated Coronary Artery Calcium Quantified by a Deep Learning Model from Radiotherapy Planning Scans Predicts Mortality in Lung Cancer. International Journal of Radiation Oncology*Biology*Physics. 105(1). S72–S72.
10.
Kolossváry, Márton, Júlia Karády, Yasuka Kikuchi, et al.. (2019). Radiomics versus Visual and Histogram-based Assessment to Identify Atheromatous Lesions at Coronary CT Angiography: An ex Vivo Study. Radiology. 293(1). 89–96. 96 indexed citations
11.
Ferencik, Maros, Michael T. Lu, Thomas Mayrhofer, et al.. (2019). Non-invasive fractional flow reserve derived from coronary computed tomography angiography in patients with acute chest pain: Subgroup analysis of the ROMICAT II trial. Journal of cardiovascular computed tomography. 13(4). 196–202. 24 indexed citations
12.
Storz, Corinna, Susanne Rospleszcz, Roberto Lorbeer, et al.. (2018). Phenotypic Multiorgan Involvement of Subclinical Disease as Quantified by Magnetic Resonance Imaging in Subjects With Prediabetes, Diabetes, and Normal Glucose Tolerance. Investigative Radiology. 53(6). 357–364. 8 indexed citations
13.
Budoff, Matthew J., Thomas Mayrhofer, Maros Ferencik, et al.. (2017). Prognostic Value of Coronary Artery Calcium in the PROMISE Study (Prospective Multicenter Imaging Study for Evaluation of Chest Pain). Circulation. 136(21). 1993–2005. 172 indexed citations
14.
Hulten, Edward, Márcio Sommer Bittencourt, Avinainder Singh, et al.. (2017). Obesity, metabolic syndrome and cardiovascular prognosis: from the Partners coronary computed tomography angiography registry. Cardiovascular Diabetology. 16(1). 14–14. 26 indexed citations
15.
Bittencourt, Márcio Sommer, Edward Hulten, Brian Ghoshhajra, et al.. (2014). Prognostic Value of Nonobstructive and Obstructive Coronary Artery Disease Detected by Coronary Computed Tomography Angiography to Identify Cardiovascular Events. Circulation Cardiovascular Imaging. 7(2). 282–291. 260 indexed citations
16.
Abdelbaky, Amr, Erin M. Corsini, Amparo L. Figueroa, et al.. (2013). Focal Arterial Inflammation Precedes Subsequent Calcification in the Same Location. Circulation Cardiovascular Imaging. 6(5). 747–754. 131 indexed citations
17.
Goehler, Alexander, Thomas Mayrhofer, Amit Pursnani, et al.. (2013). Abstract 18295: Comparison of Long Term Health and Economic Outcomes of ED Triage Strategies for Patients With Acute Chest Pain. Circulation. 128(suppl_22). 2 indexed citations
18.
Januzzi, James L., Fabian Bamberg, Hang Lee, et al.. (2010). High-Sensitivity Troponin T Concentrations in Acute Chest Pain Patients Evaluated With Cardiac Computed Tomography. Circulation. 121(10). 1227–1234. 126 indexed citations
19.
Gutiérrez, Orlando M., James L. Januzzi, Tamara Isakova, et al.. (2009). Fibroblast Growth Factor 23 and Left Ventricular Hypertrophy in Chronic Kidney Disease. Circulation. 119(19). 2545–2552. 659 indexed citations breakdown →
20.
Cury, Ricardo C., John T. Nagurney, Guido Aranha Rosito, et al.. (2008). Cardiac Magnetic Resonance With T2-Weighted Imaging Improves Detection of Patients With Acute Coronary Syndrome in the Emergency Department. Circulation. 118(8). 837–844. 164 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by J. Jeffrey Carr Breakdown of academic impact, for papers by Leslee J. Shaw Breakdown of academic impact, for papers by Ron Blankstein Breakdown of academic impact, for papers by João A.C. Lima Breakdown of academic impact, for papers by Thomas H. Marwick Breakdown of academic impact, for papers by Pamela S. Douglas Breakdown of academic impact, for papers by Raymond J. Gibbons Breakdown of academic impact, for papers by Jagat Narula Breakdown of academic impact, for papers by Robert Detrano Breakdown of academic impact, for papers by Gerhard Schüler
Rankless by CCL
2026