Roman Zeleznik

1.6k total citations · 2 hit papers
15 papers, 892 citations indexed

About

Roman Zeleznik is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Roman Zeleznik has authored 15 papers receiving a total of 892 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Cardiology and Cardiovascular Medicine and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Roman Zeleznik's work include Radiomics and Machine Learning in Medical Imaging (7 papers), Cardiac Imaging and Diagnostics (7 papers) and Cardiovascular Disease and Adiposity (4 papers). Roman Zeleznik is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (7 papers), Cardiac Imaging and Diagnostics (7 papers) and Cardiovascular Disease and Adiposity (4 papers). Roman Zeleznik collaborates with scholars based in United States, Netherlands and Germany. Roman Zeleznik's co-authors include Hugo J.W.L. Aerts, Raymond H. Mak, Chintan Parmar, Ahmed Hosny, Thibaud Coroller, Idalid Franco, Yiwen Xu, Robert J. Gillies, Johan Bussink and Patrick Großmann and has published in prestigious journals such as SHILAP Revista de lepidopterología, Radiology and Clinical Cancer Research.

In The Last Decade

Roman Zeleznik

12 papers receiving 877 citations

Hit Papers

Deep Learning Predicts Lung Cancer Treatment Response fro... 2018 2026 2020 2023 2019 2018 100 200 300 400
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. Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging
    2019 402 citations Yiwen Xu, Ahmed Hosny et al. Clinical Cancer Research profile →
  2. Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
    2018 398 citations Ahmed Hosny, Chintan Parmar et al. PLoS Medicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roman Zeleznik United States 8 716 399 271 184 82 15 892
Lise Wei United States 13 627 0.9× 218 0.5× 176 0.6× 197 1.1× 117 1.4× 24 860
Kyle J. Lafata United States 16 602 0.8× 333 0.8× 198 0.7× 160 0.9× 157 1.9× 63 892
Satish E. Viswanath United States 19 837 1.2× 519 1.3× 282 1.0× 248 1.3× 170 2.1× 90 1.4k
Jihye Yun South Korea 15 564 0.8× 323 0.8× 190 0.7× 137 0.7× 58 0.7× 36 985
Yiwen Xu United States 9 467 0.7× 392 1.0× 246 0.9× 116 0.6× 130 1.6× 22 803
Tyler Bradshaw United States 19 1.1k 1.5× 276 0.7× 119 0.4× 372 2.0× 125 1.5× 63 1.4k
Sarah A. Mattonen Canada 13 796 1.1× 457 1.1× 171 0.6× 214 1.2× 138 1.7× 36 963
Vishwa S. Parekh United States 14 722 1.0× 154 0.4× 252 0.9× 213 1.2× 128 1.6× 39 942
Jonas Teuwen Netherlands 15 962 1.3× 268 0.7× 671 2.5× 216 1.2× 120 1.5× 62 1.4k
Shufang Pei China 12 833 1.2× 212 0.5× 229 0.8× 137 0.7× 134 1.6× 23 1.0k

Countries citing papers authored by Roman Zeleznik

Since Specialization
Citations

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

Fields of papers citing papers by Roman Zeleznik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roman Zeleznik

This figure shows the co-authorship network connecting the top 25 collaborators of Roman Zeleznik. A scholar is included among the top collaborators of Roman Zeleznik 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 Roman Zeleznik. Roman Zeleznik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Zeleznik, Roman, David Maintz, Thomas Mayrhofer, et al.. (2025). Association of Epicardial Adipose Tissue Changes on Serial Chest CT Scans with Mortality: Insights from the National Lung Screening Trial. Radiology. 314(2). e240473–e240473. 3 indexed citations
2.
Foldyna, Borek, Roman Zeleznik, Vineet K. Raghu, et al.. (2024). Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers. SHILAP Revista de lepidopterología. 4(1). 44–44. 9 indexed citations
3.
Wang, Xu‐Wen, Tong Wang, Can Chen, et al.. (2023). Benchmarking omics-based prediction of asthma development in children. Respiratory Research. 24(1). 63–63. 6 indexed citations
4.
Zeleznik, Roman, David Maintz, Thomas Mayrhofer, et al.. (2023). Two-year Changes Of Epicardial Adipose Tissue Volume And Density Are Associated With Mortality In Lung Cancer Screening Population. Journal of cardiovascular computed tomography. 17(4). S46–S47.
5.
Ye, Zezhong, Jack M. Qian, Ahmed Hosny, et al.. (2022). Deep Learning–based Detection of Intravenous Contrast Enhancement on CT Scans. Radiology Artificial Intelligence. 4(3). e210285–e210285. 10 indexed citations
6.
Foldyna, Borek, Roman Zeleznik, Parastou Eslami, et al.. (2021). Small whole heart volume predicts cardiovascular events in patients with stable chest pain: insights from the PROMISE trial. European Radiology. 31(8). 6200–6210. 3 indexed citations
7.
Zeleznik, Roman, Jakob Weiß, Jana Taron, et al.. (2021). Deep-learning system to improve the quality and efficiency of volumetric heart segmentation for breast cancer. npj Digital Medicine. 4(1). 43–43. 16 indexed citations
8.
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.
9.
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
10.
Kamran, Sophia C., Thibaud Coroller, Vishesh Agrawal, et al.. (2020). The impact of quantitative CT-based tumor volumetric features on the outcomes of patients with limited stage small cell lung cancer. Radiation Oncology. 15(1). 14–14. 11 indexed citations
11.
Foldyna, Borek, Roman Zeleznik, Parastou Eslami, et al.. (2020). Epicardial Adipose Tissue in Patients With Stable Chest Pain. JACC. Cardiovascular imaging. 13(10). 2273–2275. 8 indexed citations
12.
Xu, Yiwen, Ahmed Hosny, Roman Zeleznik, et al.. (2019). Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging. Clinical Cancer Research. 25(11). 3266–3275. 402 indexed citations breakdown →
13.
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.
14.
Hosny, Ahmed, Chintan Parmar, Thibaud Coroller, et al.. (2018). Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study. PLoS Medicine. 15(11). e1002711–e1002711. 398 indexed citations breakdown →
15.
Kamran, Sophia C., Thibaud Coroller, Idalid Franco, et al.. (2017). CT-Based Radiomic Biomarker Features Predict Prognosis in Patients with Limited Stage Small Cell Lung Cancer. International Journal of Radiation Oncology*Biology*Physics. 99(2). S12–S13. 1 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 Lise Wei Breakdown of academic impact, for papers by Kyle J. Lafata Breakdown of academic impact, for papers by Satish E. Viswanath Breakdown of academic impact, for papers by Jihye Yun Breakdown of academic impact, for papers by Yiwen Xu Breakdown of academic impact, for papers by Tyler Bradshaw Breakdown of academic impact, for papers by Sarah A. Mattonen Breakdown of academic impact, for papers by Vishwa S. Parekh Breakdown of academic impact, for papers by Jonas Teuwen Breakdown of academic impact, for papers by Shufang Pei
Rankless by CCL
2026