Daniel Margolis

20.3k total citations · 7 hit papers
199 papers, 10.6k citations indexed

About

Daniel Margolis is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Rheumatology. According to data from OpenAlex, Daniel Margolis has authored 199 papers receiving a total of 10.6k indexed citations (citations by other indexed papers that have themselves been cited), including 149 papers in Pulmonary and Respiratory Medicine, 103 papers in Radiology, Nuclear Medicine and Imaging and 41 papers in Rheumatology. Recurrent topics in Daniel Margolis's work include Prostate Cancer Diagnosis and Treatment (130 papers), Prostate Cancer Treatment and Research (83 papers) and MRI in cancer diagnosis (60 papers). Daniel Margolis is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (130 papers), Prostate Cancer Treatment and Research (83 papers) and MRI in cancer diagnosis (60 papers). Daniel Margolis collaborates with scholars based in United States, Canada and United Kingdom. Daniel Margolis's co-authors include Masoom A. Haider, Peter L. Choyke, Clare M. Tempany, Katarzyna J. Macura, Leonard S. Marks, Jeffrey C. Weinreb, Jelle O. Barentsz, F. Cornud, Harriet C. Thoeny and Jiaoti Huang and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Daniel Margolis

192 papers receiving 10.5k citations

Hit Papers

PI-RADS Prostate Imaging ... 2013 2026 2017 2021 2015 2019 2016 2014 2016 500 1000 1.5k 2.0k

Author Peers

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

Author Last Decade Papers Cites
Daniel Margolis 8.6k 4.6k 2.9k 896 614 199 10.6k
Katarzyna J. Macura 5.8k 0.7× 4.7k 1.0× 1.8k 0.6× 1.2k 1.4× 538 0.9× 153 9.4k
Olivier Rouvière 7.5k 0.9× 4.3k 0.9× 2.0k 0.7× 1.1k 1.2× 1.6k 2.5× 219 10.6k
Geert Villeirs 8.1k 0.9× 4.3k 0.9× 2.1k 0.7× 832 0.9× 498 0.8× 143 9.6k
Jurgen J. Fütterer 9.7k 1.1× 6.1k 1.3× 3.4k 1.2× 1.7k 1.9× 1.4k 2.4× 267 13.1k
Hashim U. Ahmed 12.0k 1.4× 3.8k 0.8× 4.2k 1.5× 2.3k 2.5× 1.1k 1.8× 375 14.5k
Samir S. Taneja 9.2k 1.1× 3.7k 0.8× 2.7k 0.9× 1.9k 2.1× 589 1.0× 326 12.0k
Harriet C. Thoeny 5.9k 0.7× 7.3k 1.6× 1.9k 0.6× 2.3k 2.6× 442 0.7× 103 12.3k
F. Cornud 5.9k 0.7× 2.9k 0.6× 2.0k 0.7× 907 1.0× 332 0.5× 150 6.9k
Masoom A. Haider 9.9k 1.2× 7.4k 1.6× 2.3k 0.8× 1.9k 2.1× 1.8k 2.9× 258 14.9k
Aytekin Oto 3.3k 0.4× 2.8k 0.6× 857 0.3× 1.6k 1.8× 407 0.7× 236 6.4k

Countries citing papers authored by Daniel Margolis

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Margolis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Margolis

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Margolis. A scholar is included among the top collaborators of Daniel Margolis 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 Margolis. Daniel Margolis 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.
Brisbane, Wayne, Hannes Cash, Sangeet Ghai, et al.. (2025). SIU-ICUD: Comprehensive Imaging in Prostate Cancer—A Focus on MRI and Micro-Ultrasound. SHILAP Revista de lepidopterología. 6(3). 39–39. 1 indexed citations
2.
Türkbey, Barış, Henkjan Huisman, Andriy Fedorov, et al.. (2025). Requirements for AI Development and Reporting for MRI Prostate Cancer Detection in Biopsy-Naive Men: PI-RADS Steering Committee, Version 1.0. Radiology. 315(1). e240140–e240140. 1 indexed citations
3.
Wang, Jade, Jim C. Hu, Yuliya Jhanwar, et al.. (2024). Reasons for Discordance between 68Ga-PSMA-PET and Magnetic Resonance Imaging in Men with Metastatic Prostate Cancer. Cancers. 16(11). 2056–2056. 1 indexed citations
4.
Boss, Michael A., Dariya Malyarenko, Savannah C. Partridge, et al.. (2024). The QIBA Profile for Diffusion-Weighted MRI: Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker. Radiology. 313(1). e233055–e233055. 15 indexed citations
5.
McClure, Timothy, et al.. (2024). MRI–Ultrasound Fused Approach for Prostate Biopsy—How It Is Performed. Cancers. 16(7). 1424–1424. 2 indexed citations
6.
Hecht, Elizabeth M., et al.. (2024). Beyond Do No Harm: Introduction to Green Radiology. Journal of Computer Assisted Tomography. 49(2). 169–179.
7.
Kim, Heejong, Daniel Margolis, Himanshu Nagar, & Mert R. Sabuncu. (2022). Pulse Sequence Dependence of a Simple and Interpretable Deep Learning Method for Detection of Clinically Significant Prostate Cancer Using Multiparametric MRI. Academic Radiology. 30(5). 966–970. 6 indexed citations
8.
Prince, Martin R., et al.. (2022). Major hemorrhage and mortality in COVID-19 patients on therapeutic anticoagulation for venous thromboembolism. Journal of Thrombosis and Thrombolysis. 54(3). 431–437. 6 indexed citations
9.
Vlachostergios, Panagiotis J., Muhammad Junaid Niaz, Charlene Thomas, et al.. (2022). Pilot study of the diagnostic utility of 89Zr‐df‐IAB2M and 68Ga‐PSMA‐11 PET imaging and multiparametric MRI in localized prostate cancer. The Prostate. 82(4). 483–492. 13 indexed citations
10.
Margolis, Daniel, et al.. (2021). Pulmonary Embolism in Hospitalized Patients with COVID-19: A Multicenter Study. Radiology. 301(3). E426–E433. 35 indexed citations
11.
Hectors, Stefanie J., et al.. (2021). Predictors of acute deep venous thrombosis in patients hospitalized for COVID-19. Medicine. 100(38). e27216–e27216. 3 indexed citations
14.
Jeph, Sunil, et al.. (2020). PI-RADS: what is new and how to use it. Abdominal Radiology. 45(12). 3951–3960. 17 indexed citations
15.
Awamlh, Bashir Al Hussein Al, Daniel Margolis, Michael Groß, et al.. (2020). Prostate Multiparametric Magnetic Resonance Imaging Features Following Partial Gland Cryoablation. Urology. 138. 98–105. 10 indexed citations
16.
Awamlh, Bashir Al Hussein Al, Leonard S. Marks, Geoffrey A. Sonn, et al.. (2020). Multicenter analysis of clinical and MRI characteristics associated with detecting clinically significant prostate cancer in PI-RADS (v2.0) category 3 lesions. Urologic Oncology Seminars and Original Investigations. 38(7). 637.e9–637.e15. 18 indexed citations
17.
Coy, Heidi, Michael Douek, Kathleen Ruchalski, et al.. (2019). Components of Radiologic Progressive Disease Defined by RECIST 1.1 in Patients with Metastatic Clear Cell Renal Cell Carcinoma. Radiology. 292(1). 103–109. 10 indexed citations
18.
Padhani, Anwar R., Jelle O. Barentsz, Geert Villeirs, et al.. (2019). PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway. Radiology. 292(2). 464–474. 169 indexed citations
19.
Awamlh, Bashir Al Hussein Al, et al.. (2019). IDEAL Stage 2a experience with in-office, transperineal MRI/ultrasound software fusion targeted prostate biopsy. SHILAP Revista de lepidopterología. 1(1). e000025–e000025. 2 indexed citations
20.
Dregely, Isabel, Daniel Margolis, Kyunghyun Sung, et al.. (2016). Rapid quantitative T2 mapping of the prostate using three‐dimensional dual echo steady state MRI at 3T. Magnetic Resonance in Medicine. 76(6). 1720–1729. 24 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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