William Skinner

824 total citations
8 papers, 20 citations indexed

About

William Skinner is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, William Skinner has authored 8 papers receiving a total of 20 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Surgery and 6 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in William Skinner's work include Cardiac Imaging and Diagnostics (8 papers), Coronary Interventions and Diagnostics (7 papers) and Acute Myocardial Infarction Research (4 papers). William Skinner is often cited by papers focused on Cardiac Imaging and Diagnostics (8 papers), Coronary Interventions and Diagnostics (7 papers) and Acute Myocardial Infarction Research (4 papers). William Skinner collaborates with scholars based in Netherlands, Italy and United States. William Skinner's co-authors include Gary S. Mintz, Varinder Singh, Rebecca Torguson, Cheng Zhang, Ron Waksman, Gheorghe Doros, Tim ten Cate, Carlo Di Mario, Ziad A. Ali and Héctor M. García‐García and has published in prestigious journals such as The American Journal of Cardiology, Atherosclerosis and European Heart Journal - Cardiovascular Imaging.

In The Last Decade

William Skinner

7 papers receiving 20 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
William Skinner Netherlands	3	12	12	11	4	3	8	20
Libor Nechvátal Czechia	3	7 0.6×	7 0.6×	11 1.0×	3 0.8×		4	14
Nikolaos Östlund-Papadogeorgos Sweden	3	11 0.9×	10 0.8×	15 1.4×		1 0.3×	4	16
Wael El-Kilany Egypt	3	11 0.9×	12 1.0×	17 1.5×			6	20
Fabrice Prunier France	3	12 1.0×	13 1.1×	26 2.4×	1 0.3×	2 0.7×	4	30
Michael Pitt United Kingdom	2	8 0.7×	12 1.0×	12 1.1×			4	19
María Ángeles Alonso García United Kingdom	2	10 0.8×	12 1.0×	16 1.5×	1 0.3×		2	23
Lilian Mazza Barbosa United States	2	17 1.4×	6 0.5×	18 1.6×	1 0.3×	1 0.3×	2	24
Eul‐Soon Im South Korea	2	9 0.8×	5 0.4×	9 0.8×			2	10
Loukianos S. Rallidis United Kingdom	2	9 0.8×	8 0.7×	14 1.3×	1 0.3×	1 0.3×	2	20
Tsuei-Yuan Huang Taiwan	3	13 1.1×	9 0.8×	12 1.1×			3	15

Countries citing papers authored by William Skinner

Since Specialization

Citations

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

Fields of papers citing papers by William Skinner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Skinner

This figure shows the co-authorship network connecting the top 25 collaborators of William Skinner. A scholar is included among the top collaborators of William Skinner 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 William Skinner. William Skinner 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

Torguson, Rebecca, Gary S. Mintz, Carlo Di Mario, et al.. (2023). Disparities among Black and White patients in plaque burden and composition and long-term impact. Cardiovascular revascularization medicine. 55. 28–32. 1 indexed citations

Roes, Kit C. B., Carlo Di Mario, Varinder Singh, et al.. (2022). Near-infrared spectroscopy predicts events in men and women: Results from the Lipid Rich Plaque study. IJC Heart & Vasculature. 39. 100985–100985.

Mario, Carlo Di, Rebecca Torguson, Ziad A. Ali, et al.. (2021). Lipid-rich plaques detected by near-infrared spectroscopy predict coronary events irrespective of age: A Lipid Rich Plaque sub-study. Atherosclerosis. 334. 17–22. 4 indexed citations

Torguson, Rebecca, Evan Shlofmitz, Gary S. Mintz, et al.. (2021). Frequency of Lipid-Rich Coronary Plaques in Stable Angina Pectoris versus Acute Coronary Syndrome (from the Lipid Rich Plaque Study). The American Journal of Cardiology. 158. 1–5. 1 indexed citations

Mintz, Gary S., Rebecca Torguson, Carlo Di Mario, et al.. (2021). Non-Culprit MACE Rate in LRP: The Influence of Optimal Medical Therapy Using DAPT and Statins. Cardiovascular revascularization medicine. 37. 92–96. 3 indexed citations

Kuku, Kayode O., Héctor M. García‐García, Gheorghe Doros, et al.. (2021). Predicting future left anterior descending artery events from non-culprit lesions: insights from the Lipid-Rich Plaque study. European Heart Journal - Cardiovascular Imaging. 23(10). 1365–1372. 2 indexed citations

Mario, Carlo Di, Rebecca Torguson, Tim ten Cate, et al.. (2021). Greater plaque burden and cholesterol content may explain an increased incidence of non-culprit events in diabetic patients: a Lipid-Rich Plaque substudy. European Heart Journal - Cardiovascular Imaging. 23(8). 1098–1107. 2 indexed citations

Skinner, William, et al.. (1982). Cardiac arrest during exercise training after myocardial infarction.. PubMed. 46(5). 239–43. 7 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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