Danielle M. Dargis

427 total citations
8 papers, 150 citations indexed

About

Danielle M. Dargis is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Biomedical Engineering. According to data from OpenAlex, Danielle M. Dargis has authored 8 papers receiving a total of 150 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Surgery and 3 papers in Biomedical Engineering. Recurrent topics in Danielle M. Dargis's work include Cardiac Imaging and Diagnostics (5 papers), Advanced X-ray and CT Imaging (3 papers) and Coronary Interventions and Diagnostics (3 papers). Danielle M. Dargis is often cited by papers focused on Cardiac Imaging and Diagnostics (5 papers), Advanced X-ray and CT Imaging (3 papers) and Coronary Interventions and Diagnostics (3 papers). Danielle M. Dargis collaborates with scholars based in United States, Germany and China. Danielle M. Dargis's co-authors include U. Joseph Schoepf, Xiuli Li, Zhao Shi, Chengwei Pan, Long Jiang Zhang, Qianqian Ni, Rock H. Savage, Guangming Lu, Tilman Emrich and Gilberto J. Aquino and has published in prestigious journals such as American Journal of Neuroradiology, Journal of Magnetic Resonance Imaging and International Journal of Cardiology.

In The Last Decade

Danielle M. Dargis

8 papers receiving 148 citations

Peers

Danielle M. Dargis

RNMI

PRM

NEURO

CCM

BE

Praneeta R. Konduri Netherlands

Manon L. Tolhuisen Netherlands

Ivan A. Blokhin Russia

Jianyong Wei China

Yuriko Yoshida Japan

Lennard Wolff Netherlands

Alexander R. Podgorsak United States

Joshua Lampert United States

Rania Abdelkhaleq United States

Jay Gajera Australia

Praneeta R. Konduri Netherlands

Danielle M. Dargis

33 ×0.4

RNMI

86 ×1.2

PRM

57 ×1.0

NEURO

16 ×0.6

CCM

23 ×0.9

BE

Citations per year, relative to Danielle M. Dargis Danielle M. Dargis (= 1×) peers Praneeta R. Konduri

Countries citing papers authored by Danielle M. Dargis

Since Specialization

Citations

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

Fields of papers citing papers by Danielle M. Dargis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danielle M. Dargis. 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 Danielle M. Dargis. The network helps show where Danielle M. Dargis may publish in the future.

Co-authorship network of co-authors of Danielle M. Dargis

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

All Works

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8 of 8 papers shown

1.

Abadia, Andres F., Gilberto J. Aquino, U. Joseph Schoepf, et al.. (2022). Automated Dual-energy Computed Tomography-based Extracellular Volume Estimation for Myocardial Characterization in Patients With Ischemic and Nonischemic Cardiomyopathy. Journal of Thoracic Imaging. 37(5). 307–314. 9 indexed citations

2.

Abadia, Andres F., Gilberto J. Aquino, U. Joseph Schoepf, et al.. (2022). Automated Dual-energy Computed Tomography-based Extracellular Volume Estimation for Myocardial Characterization in Patients With Ischemic and Nonischemic Cardiomyopathy.. PubMed. 37(5). 307–314. 6 indexed citations

3.

Varga‐Szemes, Ákos, Moritz C. Halfmann, U. Joseph Schoepf, et al.. (2022). Highly Accelerated Compressed‐Sensing 4D Flow for Intracardiac Flow Assessment. Journal of Magnetic Resonance Imaging. 58(2). 496–507. 10 indexed citations

4.

Varga‐Szemes, Ákos, U. Joseph Schoepf, Pál Maurovich‐Horvat, et al.. (2021). Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve. International Journal of Cardiology. 331. 307–315. 8 indexed citations

5.

Abadia, Andres F., Madison Kocher, U. Joseph Schoepf, et al.. (2021). Diagnostic Accuracy and Performance of Artificial Intelligence in Detecting Lung Nodules in Patients With Complex Lung Disease. Journal of Thoracic Imaging. 37(3). 154–161. 30 indexed citations

6.

Shi, Zhao, U. Joseph Schoepf, Rock H. Savage, et al.. (2020). Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives. American Journal of Neuroradiology. 41(3). 373–379. 68 indexed citations

7.

Brandt, Verena, Tilman Emrich, U. Joseph Schoepf, et al.. (2020). Ischemia and outcome prediction by cardiac CT based machine learning. International journal of cardiac imaging. 36(12). 2429–2439. 15 indexed citations

8.

Lee, Heon, Tilman Emrich, U. Joseph Schoepf, et al.. (2020). Artificial Intelligence in Cardiac CT: Automated Calcium Scoring and Plaque Analysis. Current Cardiovascular Imaging Reports. 13(11). 4 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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