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D-Index & Metrics

Medicine

D-Index
96
Citations
32215
World Ranking
9716
National Ranking
5001

Piotr J. Slomka publication distribution in Medicine in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Medicine in 2026. The highlighted bar marks where Piotr J. Slomka sits on this spectrum.

101–120 publications: 5 scientists 121–140 publications: 26 scientists 141–160 publications: 73 scientists 161–180 publications: 155 scientists 181–200 publications: 230 scientists 201–220 publications: 363 scientists 221–240 publications: 487 scientists 241–260 publications: 545 scientists 261–280 publications: 722 scientists 281–300 publications: 768 scientists 301–320 publications: 834 scientists 321–340 publications: 895 scientists 341–360 publications: 922 scientists 361–380 publications: 838 scientists 381–400 publications: 861 scientists 401–420 publications: 918 scientists 421–440 publications: 806 scientists 441–460 publications: 771 scientists 461–480 publications: 751 scientists 481–500 publications: 713 scientists 501–520 publications: 617 scientists 521–540 publications: 611 scientists 541–560 publications: 537 scientists 561–580 publications: 504 scientists 581–600 publications: 509 scientists 601–620 publications: 396 scientists 621–640 publications: 386 scientists 641–660 publications: 371 scientists 661–680 publications: 340 scientists 681–700 publications: 336 scientists 701–720 publications: 307 scientists 721–740 publications: 259 scientists 741–760 publications: 230 scientists 761–780 publications: 228 scientists 781–800 publications: 217 scientists 801–820 publications: 204 scientists 821–840 publications: 186 scientists 841–860 publications: 177 scientists 861–880 publications: 155 scientists 881–900 publications: 139 scientists 901–920 publications: 145 scientists 921–940 publications: 116 scientists 941–960 publications: 133 scientists 961–980 publications: 91 scientists 981–1,000 publications: 96 scientists 1,001–1,020 publications: 77 scientists 1,021–1,040 publications: 70 scientists 1,041–1,060 publications: 63 scientists 1,061–1,080 publications: 77 scientists 1,081–1,100 publications: 49 scientists 1,101–1,120 publications: 54 scientists 1,121–1,140 publications: 49 scientists 1,141–1,160 publications: 51 scientists 1,161–1,180 publications: 35 scientists 1,181–1,200 publications: 39 scientists 1,201–1,220 publications: 26 scientists 1,221–1,240 publications: 37 scientists 1,241–1,260 publications: 36 scientists 1,261–1,280 publications: 27 scientists 1,281–1,300 publications: 32 scientists 1,301–1,320 publications: 28 scientists 1,321–1,340 publications: 17 scientists 1,341–1,360 publications: 30 scientists 1,361–1,380 publications: 28 scientists 1,381–1,400 publications: 17 scientists 1,401–1,420 publications: 21 scientists 1,421–1,440 publications: 15 scientists 1,441–1,460 publications: 12 scientists 1,461–1,480 publications: 12 scientists 1,481–1,500 publications: 18 scientists 1,501–1,520 publications: 14 scientists 1,521–1,540 publications: 17 scientists 1,541–1,560 publications: 15 scientists 1,561–1,580 publications: 6 scientists 1,581–1,600 publications: 2 scientists 1,601–1,620 publications: 12 scientists 1,621–1,640 publications: 11 scientists 1,641–1,660 publications: 8 scientists 1,661–1,680 publications: 5 scientists 1,681–1,700 publications: 5 scientists 1,701–1,720 publications: 10 scientists 1,721–1,740 publications: 12 scientists 1,741–1,760 publications: 14 scientists 1,761–1,780 publications: 6 scientists 1,781–1,795 publications: 5 scientists 1,796+ publications: 100 scientists
101 publications 1,796+

This scientist: 699 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,796 publications or more.

Piotr J. Slomka D-index placement in Medicine in 2026

The chart shows the D-index (discipline H-index) distribution of Medicine scientists ranked by Research.com in 2026. The highlighted bar marks where Piotr J. Slomka sits on this spectrum.

70–71 D-Index: 226 scientists 72–73 D-Index: 391 scientists 74–75 D-Index: 574 scientists 76–77 D-Index: 730 scientists 78–79 D-Index: 891 scientists 80–81 D-Index: 972 scientists 82–83 D-Index: 1,027 scientists 84–85 D-Index: 1,003 scientists 86–87 D-Index: 960 scientists 88–89 D-Index: 970 scientists 90–91 D-Index: 922 scientists 92–93 D-Index: 839 scientists 94–95 D-Index: 808 scientists 96–97 D-Index: 779 scientists 98–99 D-Index: 668 scientists 100–101 D-Index: 611 scientists 102–103 D-Index: 630 scientists 104–105 D-Index: 513 scientists 106–107 D-Index: 541 scientists 108–109 D-Index: 445 scientists 110–111 D-Index: 429 scientists 112–113 D-Index: 400 scientists 114–115 D-Index: 393 scientists 116–117 D-Index: 318 scientists 118–119 D-Index: 302 scientists 120–121 D-Index: 287 scientists 122–123 D-Index: 255 scientists 124–125 D-Index: 256 scientists 126–127 D-Index: 252 scientists 128–129 D-Index: 230 scientists 130–131 D-Index: 179 scientists 132–133 D-Index: 168 scientists 134–135 D-Index: 163 scientists 136–137 D-Index: 159 scientists 138–139 D-Index: 134 scientists 140–141 D-Index: 134 scientists 142–143 D-Index: 118 scientists 144–145 D-Index: 109 scientists 146–147 D-Index: 106 scientists 148–149 D-Index: 74 scientists 150–151 D-Index: 79 scientists 152–153 D-Index: 80 scientists 154–155 D-Index: 87 scientists 156–157 D-Index: 57 scientists 158–159 D-Index: 74 scientists 160–161 D-Index: 69 scientists 162–163 D-Index: 60 scientists 164–165 D-Index: 53 scientists 166–167 D-Index: 39 scientists 168–169 D-Index: 42 scientists 170–171 D-Index: 32 scientists 172–173 D-Index: 39 scientists 174–175 D-Index: 40 scientists 176–177 D-Index: 28 scientists 178–179 D-Index: 19 scientists 180–181 D-Index: 23 scientists 182–183 D-Index: 31 scientists 184–185 D-Index: 18 scientists 186–187 D-Index: 20 scientists 188–189 D-Index: 22 scientists 190–191 D-Index: 13 scientists 192–193 D-Index: 21 scientists 194–195 D-Index: 12 scientists 196–197 D-Index: 12 scientists 198–199 D-Index: 14 scientists 200–201 D-Index: 15 scientists 202–203 D-Index: 13 scientists 204–205 D-Index: 10 scientists 206–207 D-Index: 8 scientists 208–209 D-Index: 4 scientists 210–211 D-Index: 12 scientists 212–213 D-Index: 11 scientists 214–215 D-Index: 10 scientists 216 D-Index: 4 scientists 217+ D-Index: 98 scientists
70 D-Index 217+

This scientist: 96 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 217 D-Index or more.

Overview

Piotr J. Slomka is affiliated with the Cedars-Sinai Medical Center in the United States and has contributed extensively to research in the field of medicine, with a particular focus on radiology, nuclear medicine, imaging, and cardiology.

The primary areas of their research encompass:

  • Cardiac Imaging and Diagnostics
  • Advanced X-ray and CT Imaging
  • Medical Imaging Techniques and Applications
  • Coronary Interventions and Diagnostics
  • Advanced MRI Techniques and Applications
  • Cardiovascular Disease and Adiposity
  • Cardiovascular Function and Risk Factors

Slomka's frequent co-authors include:

  • Damini Dey
  • Daniel S. Berman
  • Robert J.H. Miller
  • Marc R. Dweck
  • David E. Newby

Key venues where Slomka has published research are:

  • Journal of Nuclear Cardiology
  • Journal of the American College of Cardiology
  • Journal of cardiovascular computed tomography
  • JACC. Cardiovascular imaging
  • Journal of Nuclear Medicine

Significant papers authored or co-authored by Slomka include:

  • Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction, 2020, Circulation
  • Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist, 2020, JACC. Cardiovascular imaging
  • Myocardial Infarction Associates With a Distinct Pericoronary Adipose Tissue Radiomic Phenotype, 2020, JACC. Cardiovascular imaging
  • Deep Learning-Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects, 2020, Circulation Cardiovascular Imaging
  • Coronary 18F-Sodium Fluoride Uptake Predicts Outcomes in Patients With Coronary Artery Disease, 2020, Journal of the American College of Cardiology

The body of Slomka's work is rooted heavily in cardiovascular imaging techniques and diagnostics, with an emphasis on advanced imaging modalities such as CT, MRI, and specialized nuclear cardiology methods. Their research addresses the quantification and risk prediction related to coronary artery disease and myocardial infarction, frequently applying machine learning and radiomic analysis.

With over 1,000 publications in the medicine field, including more than 500 in radiology and nuclear medicine, Slomka's contributions intersect biomedical engineering and cardiology, reflecting a multidisciplinary approach to cardiovascular disease diagnosis and management.

Best Publications

  • Optimal Medical Therapy With or Without Percutaneous Coronary Intervention to Reduce Ischemic Burden Results From the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) Trial Nuclear Substudy

    Leslee J. Shaw;Daniel S. Berman;David J. Maron;G. B. John Mancini

  • Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis.

    Manish Motwani;Damini Dey;Daniel S. Berman;Guido Germano

  • Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review.

    Damini Dey;Piotr J. Slomka;Paul Leeson;Dorin Comaniciu

  • Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction: Results From the Multicenter SCOT-HEART Trial (Scottish Computed Tomography of the HEART).

    Michelle C. Williams;Jacek Kwiecinski;Mhairi Doris;Priscilla McElhinney

  • Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging

    Subhi J. Al'Aref;Khalil Anchouche;Gurpreet Singh;Piotr J. Slomka

  • Underestimation of extent of ischemia by gated SPECT myocardial perfusion imaging in patients with left main coronary artery disease

    Daniel S Berman;Xingping Kang;Piotr J Slomka;James Gerlach

  • Aortic Size Assessment by Noncontrast Cardiac Computed Tomography: Normal Limits by Age, Gender, and Body Surface Area

    Arik Wolak;Heidi Gransar;Louise E.J. Thomson;John D. Friedman

  • Single Photon Emission Computed Tomography (SPECT) Myocardial Perfusion Imaging Guidelines: Instrumentation, Acquisition, Processing, and Interpretation

    Sharmila Dorbala;Karthik Ananthasubramaniam;Ian S. Armstrong;Panithaya Chareonthaitawee

  • Reversible ischemia around intracerebral hemorrhage: a single-photon emission computerized tomography study.

    M Shahid Siddique;Helen M Fernandes;Thomas D Wooldridge;John D Fenwick

  • Clinical Quantification of Myocardial Blood Flow Using PET: Joint Position Paper of the SNMMI Cardiovascular Council and the ASNC.

    Venkatesh L. Murthy;Timothy M. Bateman;Rob S. Beanlands;Daniel S. Berman

  • Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study

    Julian Betancur;Frederic Commandeur;Mahsaw Motlagh;Tali Sharir

  • Pericardial Fat Burden on ECG-Gated Noncontrast CT in Asymptomatic Patients Who Subsequently Experience Adverse Cardiovascular Events

    Victor Y. Cheng;Damini Dey;Damini Dey;Balaji Tamarappoo;Ryo Nakazato

  • Automated quantification of myocardial perfusion SPECT using simplified normal limits

    Piotr J. Slomka;Piotr J. Slomka;Hidetaka Nishina;Daniel S. Berman;Daniel S. Berman;Cigdem Akincioglu

  • Quantitation in gated perfusion SPECT imaging: the Cedars-Sinai approach.

    Guido Germano;Guido Germano;Paul B. Kavanagh;Piotr J. Slomka;Piotr J. Slomka;Serge D. Van Kriekinge;Serge D. Van Kriekinge

  • Advances in technical aspects of myocardial perfusion SPECT imaging.

    Piotr J. Slomka;James A. Patton;Daniel S. Berman;Guido Germano

  • Baseline stress myocardial perfusion imaging results and outcomes in patients with stable ischemic heart disease randomized to optimal medical therapy with or without percutaneous coronary intervention

    Leslee J. Shaw;William S. Weintraub;David J. Maron;Pamela M. Hartigan

  • Quantification of Myocardial Perfusion Reserve Using Dynamic SPECT Imaging in Humans: A Feasibility Study

    Simona Ben-Haim;Simona Ben-Haim;Venkatesh L. Murthy;Venkatesh L. Murthy;Christopher Breault;Rayjanah Allie

  • Pericoronary Adipose Tissue Computed Tomography Attenuation and High-Risk Plaque Characteristics in Acute Coronary Syndrome Compared With Stable Coronary Artery Disease

    Markus Goeller;Markus Goeller;Stephan Achenbach;Sebastien Cadet;Alan C. Kwan

  • Automated three-dimensional quantification of noncalcified coronary plaque from coronary CT angiography: comparison with intravascular US.

    Damini Dey;Tiziano Schepis;Mohamed Marwan;Piotr J Slomka

  • Cannabis induced dopamine release: an in-vivo SPECT study.

    Lakshmi N.P Voruganti;Lakshmi N.P Voruganti;Piotr Slomka;Pamela Zabel;Adel Mattar

Frequent Co-Authors

Daniel S. Berman
Daniel S. Berman Cedars-Sinai Medical Center
Damini Dey
Damini Dey Cedars-Sinai Medical Center
Guido Germano
Guido Germano Cedars-Sinai Medical Center
Sean W. Hayes
Sean W. Hayes Cedars-Sinai Medical Center
John D. Friedman
John D. Friedman Cedars-Sinai Medical Center
David E. Newby
David E. Newby University of Edinburgh
Marc R. Dweck
Marc R. Dweck University of Edinburgh
Leslee J. Shaw
Leslee J. Shaw Icahn School of Medicine at Mount Sinai
Sharmila Dorbala
Sharmila Dorbala Brigham and Women's Hospital
Stephan Achenbach
Stephan Achenbach University of Erlangen-Nuremberg

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