D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Medicine D-index 80 Citations 20,843 572 World Ranking 11988 National Ranking 6270

Overview

What is he best known for?

The fields of study he is best known for:

  • Internal medicine
  • Radiology
  • Artificial intelligence

Nuclear medicine, Perfusion, Coronary artery disease, Myocardial perfusion imaging and Radiology are his primary areas of study. His biological study spans a wide range of topics, including Hemodynamics, Area under the curve, Ejection fraction and Perfusion scanning. His work in Perfusion tackles topics such as Artificial intelligence which are related to areas like Medical physics.

His Coronary artery disease study focuses on Cardiology and Internal medicine. His study in Myocardial perfusion imaging is interdisciplinary in nature, drawing from both Machine learning, Gated SPECT, Blood flow and Emission computed tomography. His Radiology study integrates concerns from other disciplines, such as Pericardium, Clinical trial, Coronary ct angiography, Electrocardiography and Adipose tissue.

His most cited work include:

  • 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 (1257 citations)
  • Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis. (260 citations)
  • Underestimation of extent of ischemia by gated SPECT myocardial perfusion imaging in patients with left main coronary artery disease (257 citations)

What are the main themes of his work throughout his whole career to date?

Piotr J. Slomka focuses on Nuclear medicine, Internal medicine, Cardiology, Coronary artery disease and Perfusion. His Nuclear medicine study incorporates themes from Tomography, Radiology and Perfusion scanning. The various areas that Piotr J. Slomka examines in his Radiology study include Coronary ct angiography and Artery, Coronary arteries.

His work in the fields of Internal medicine, such as Myocardial infarction, Mace and Asymptomatic, overlaps with other areas such as In patient. His Coronary artery disease research is multidisciplinary, relying on both Angiography, Stenosis and CAD. He studies Myocardial perfusion imaging which is a part of Perfusion.

He most often published in these fields:

  • Nuclear medicine (54.04%)
  • Internal medicine (43.90%)
  • Cardiology (42.95%)

What were the highlights of his more recent work (between 2019-2021)?

  • Internal medicine (43.90%)
  • Cardiology (42.95%)
  • Coronary artery disease (41.36%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Internal medicine, Cardiology, Coronary artery disease, Myocardial perfusion imaging and Nuclear medicine. His work on Myocardial infarction, Mace and Epicardial adipose tissue is typically connected to In patient as part of general Internal medicine study, connecting several disciplines of science. Piotr J. Slomka has researched Cardiology in several fields, including Calcification and Hazard ratio.

He interconnects Computed tomography angiography, Angiography, Confidence interval, Positron emission tomography and Coronary computed tomography angiography in the investigation of issues within Coronary artery disease. His study with Myocardial perfusion imaging involves better knowledge in Perfusion. His Nuclear medicine research is multidisciplinary, incorporating perspectives in Repeatability, Blood flow and Reproducibility.

Between 2019 and 2021, his most popular works were:

  • 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). (58 citations)
  • Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT). (31 citations)
  • Coronary 18F-Sodium Fluoride Uptake Predicts Outcomes in Patients With Coronary Artery Disease. (25 citations)

In his most recent research, the most cited papers focused on:

  • Internal medicine
  • Radiology
  • Artificial intelligence

His primary areas of investigation include Internal medicine, Coronary artery disease, Cardiology, Positron emission tomography and Nuclear medicine. The Epicardial adipose tissue research Piotr J. Slomka does as part of his general Internal medicine study is frequently linked to other disciplines of science, such as In patient, Checklist and Multidisciplinary approach, therefore creating a link between diverse domains of science. A large part of his Coronary artery disease studies is devoted to Myocardial perfusion imaging.

While the research belongs to areas of Myocardial perfusion imaging, he spends his time largely on the problem of Mace, intersecting his research to questions surrounding Single-photon emission computed tomography, Revascularization, Perfusion, Training set and Stress imaging. His research in Cardiology tackles topics such as Hazard ratio which are related to areas like Ischemia. His specific area of interest is Nuclear medicine, where Piotr J. Slomka studies PET-CT.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

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.
Circulation (2008)

2118 Citations

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.
European Heart Journal (2016)

457 Citations

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.
Journal of Nuclear Cardiology (2007)

333 Citations

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

M Shahid Siddique;Helen M Fernandes;Thomas D Wooldridge;John D Fenwick.
Journal of Neurosurgery (2002)

326 Citations

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.
Jacc-cardiovascular Imaging (2008)

303 Citations

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

Damini Dey;Piotr J. Slomka;Paul Leeson;Dorin Comaniciu.
Journal of the American College of Cardiology (2019)

278 Citations

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.
Jacc-cardiovascular Imaging (2010)

276 Citations

Advances in technical aspects of myocardial perfusion SPECT imaging.

Piotr J. Slomka;James A. Patton;Daniel S. Berman;Guido Germano.
Journal of Nuclear Cardiology (2009)

271 Citations

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.
European Heart Journal (2019)

260 Citations

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.
Journal of Nuclear Cardiology (2004)

260 Citations

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