Thomas Song

1.5k citations
31 papers · 997 · h-index 15

Impact in

Papers in

Thomas Song

26 papers receiving 977 citations

Peers

Thomas Song
Comparison fields: 5 of 83
  • Health Informatics 54
  • Internal Medicine 87
  • Radiology, Nuclear Medicine and Imaging 456
  • Cardiology and Cardiovascular Medicine 427
  • Critical Care and Intensive Care Medicine 49
Replace Kwang Nam Jin with:
Kwang Nam Jin South Korea
Jae‐Kwang Lim South Korea
Thomas Weikert Switzerland
Prashant Nagpal United States
Satinder P. Singh United States
Adele Valentini Italy
César Higa Nomura Brazil
Leor Perl Israel
Marta Zerunian Italy
Adam Russak United States
Thomas Song relative to Kwang Nam Jin South Korea Kwang Nam Jin's profile →
Citations per field
00.5×2.9×
Kwang Nam Jin · 1×
Citations per year

Countries citing papers authored by Thomas Song

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Thomas Song, 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 Thomas Song Line = papers co-authored together Thomas Song links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020176
2 2017122
3 2016107
4 202095
5 200988
6 201688
7 201859
8 201242
9 201539
10 201036
11 201632
12 202021
13
Coronary computed tomography angiography in dialysis patients undergoing pre-renal transplantation cardiac risk stratification.
201020
14 200719
15 202016
16 200712
17 20128
18 20194
19 20223
20 20202

About Thomas Song

Thomas Song is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Surgery and Epidemiology, having authored 31 papers that have together received 997 indexed citations. Recurring topics across this work include Cardiac Valve Diseases and Treatments (9 papers), Cardiac Imaging and Diagnostics (8 papers), Infective Endocarditis Diagnosis and Management (6 papers), Cardiac Arrhythmias and Treatments (5 papers), Atrial Fibrillation Management and Outcomes (5 papers), Lung Cancer Diagnosis and Treatment (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Health Informatics (54 citations), Internal Medicine (87 citations), Radiology, Nuclear Medicine and Imaging (456 citations), Cardiology and Cardiovascular Medicine (427 citations) and Critical Care and Intensive Care Medicine (49 citations). Thomas Song has collaborated with scholars based in United States, United Kingdom and South Korea. Frequent co-authors include Dee Dee Wang, Milan Pantelic, Adam B. Greenbaum, William W. O’Neill, Marvin H. Eng, Eric Myers, Jeffrey Nadig, Patrick Karabon, Janet Wyman and David L. Spizarny. Their work appears in journals such as Academic Radiology, JACC. Cardiovascular imaging, Journal of the American College of Cardiology, Radiology and Catheterization and Cardiovascular Interventions.

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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