Daniel S. Berman

114.7k citations
1.2k papers · 56.0k · 17 hit papers · h-index 120

Impact in

Papers in

Daniel S. Berman

1.1k papers receiving 54.2k citations

Daniel S. Berman's Hit Papers

A Survey of Deep Learning Methods for Cyber Security 2019 · 354 citations
3540+10+20Years since publication2505007501000

Peers

Daniel S. Berman
Comparison fields: 5 of 196
  • Radiology, Nuclear Medicine and Imaging 35.0k
  • Cardiology and Cardiovascular Medicine 18.7k
  • Surgery 10.1k
  • Health Informatics 268
  • Biomedical Engineering 7.6k
Replace David A. Bluemke with:
David A. Bluemke United States
Udo Hoffmann United States
Stephan Achenbach Germany
Leslee J. Shaw United States
João A.C. Lima United States
Thomas H. Marwick Australia
Matthew J. Budoff United States
Jagat Narula United States
James K. Min United States
James D. Thomas United States
Daniel S. Berman relative to David A. Bluemke United States David A. Bluemke's profile →
Citations per field
00.5×1.5×2.3×
David A. Bluemke · 1×
Citations per year

Countries citing papers authored by Daniel S. Berman

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. Berman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel S. Berman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel S. Berman Line = papers co-authored together Daniel S. Berman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 1.2k papers — load more, or switch the sort, to bring in the rest.

#Work
1
Intracoronary cardiosphere-derived cells for heart regeneration after myocardial infarction (CADUCEUS): a prospective, randomised phase 1 trial
Hit paper breakdown →
20121040
2
Long-Term Prognosis Associated With Coronary Calcification
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2007994
3
Automatic quantification of ejection fraction from gated myocardial perfusion SPECT.
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1995987
4
Comparison of the Short-Term Survival Benefit Associated With Revascularization Compared With Medical Therapy in Patients With No Prior Coronary Artery Disease Undergoing Stress Myocardial Perfusion Single Photon Emission Computed Tomography
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2003982
5
Incremental Prognostic Value of Myocardial Perfusion Single Photon Emission Computed Tomography for the Prediction of Cardiac Death
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1998886
6
Diagnostic Accuracy of Fractional Flow Reserve From Anatomic CT Angiography
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2012798
7
The VIVA Trial
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2003797
8
Prognostic Value of Multidetector Coronary Computed Tomographic Angiography for Prediction of All-Cause Mortality
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2007720
9
Prognostic Value of Cardiac Risk Factors and Coronary Artery Calcium Screening for All-Cause Mortality
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2003664
10
Exercise Myocardial Perfusion SPECT in Patients Without Known Coronary Artery Disease
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1996628
11
Mental Stress and the Induction of Silent Myocardial Ischemia in Patients with Coronary Artery Disease
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1988552
12
Technetium-99m hexakis 2-methoxyisobutyl isonitrile: human biodistribution, dosimetry, safety, and preliminary comparison to thallium-201 for myocardial perfusion imaging.
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1989491
13
ACCF/ASNC/ACR/AHA/ASE/SCCT/SCMR/SNM 2009 Appropriate Use Criteria for Cardiac Radionuclide Imaging
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2009462
14
CAD-RADSTM Coronary Artery Disease – Reporting and Data System. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology
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2016459
15 1995442
16 1993431
17 2004416
18 1999410
19 2009391
20
CAD-RADS™: Coronary Artery Disease – Reporting and Data System
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2016383

About Daniel S. Berman

Daniel S. Berman is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Biomedical Engineering, Surgery and Pulmonary and Respiratory Medicine, having authored 1.2k papers that have together received 56.0k indexed citations. Recurring topics across this work include Cardiac Imaging and Diagnostics (794 papers), Advanced X-ray and CT Imaging (161 papers), Advanced MRI Techniques and Applications (152 papers), Medical Imaging Techniques and Applications (147 papers), Cardiovascular Function and Risk Factors (81 papers), Coronary Interventions and Diagnostics (80 papers), Cardiovascular Disease and Adiposity (76 papers) and Acute Myocardial Infarction Research (60 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (35.0k citations), Cardiology and Cardiovascular Medicine (18.7k citations), Surgery (10.1k citations), Health Informatics (268 citations) and Biomedical Engineering (7.6k citations). Daniel S. Berman has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Leslee J. Shaw, John D. Friedman, Guido Germano, Piotr J. Slomka, Sean W. Hayes, Rory Hachamovitch, Ishac Cohen, Alan Rozanski, Jamshid Maddahi and Hosen Kiat. Their work appears in journals such as Journal of the American College of Cardiology, Journal of Nuclear Cardiology, The American Journal of Cardiology, JACC. Cardiovascular imaging and Journal of cardiovascular computed tomography.

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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