Michelle C. Williams

14.3k total citations · 4 hit papers
200 papers, 5.3k citations indexed

About

Michelle C. Williams is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, Michelle C. Williams has authored 200 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 154 papers in Radiology, Nuclear Medicine and Imaging, 83 papers in Cardiology and Cardiovascular Medicine and 55 papers in Biomedical Engineering. Recurrent topics in Michelle C. Williams's work include Cardiac Imaging and Diagnostics (144 papers), Advanced X-ray and CT Imaging (53 papers) and Coronary Interventions and Diagnostics (41 papers). Michelle C. Williams is often cited by papers focused on Cardiac Imaging and Diagnostics (144 papers), Advanced X-ray and CT Imaging (53 papers) and Coronary Interventions and Diagnostics (41 papers). Michelle C. Williams collaborates with scholars based in United Kingdom, United States and New Zealand. Michelle C. Williams's co-authors include David E. Newby, Marc R. Dweck, Edwin J.R. van Beek, Alastair J. Moss, Edward Nicol, Anoop Shah, Nikhil Joshi, James H.F. Rudd, Philip D Adamson and Giles Roditi and has published in prestigious journals such as The Lancet, Journal of the American College of Cardiology and Stroke.

In The Last Decade

Michelle C. Williams

189 papers receiving 5.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

18F-fluoride positron emission tomography for identification of ruptured and high-risk coronary atherosclerotic plaques: a prospective clinical trial

2013 660 citations Nikhil Joshi, Michelle C. Williams et al. profile →
Coronary Artery Plaque Characteristics Associated With Adverse Outcomes in the SCOT-HEART Study

2019 354 citations Michelle C. Williams, Alastair J. Moss et al. profile →
Coronary Arterial 18F-Sodium Fluoride Uptake

2012 353 citations Marc R. Dweck, Nikhil Joshi et al. profile →
Association of Lipoprotein(a) With Atherosclerotic Plaque Progression

2022 99 citations Evangelos Tzolos, Mohammed N. Meah et al. profile →

Peers

Michelle C. Williams

RNMI

CCM

SURGE

PRM

Daniel S. Hippe United States

Julie M. Miller United States

Eugenio Santoro Italy

Jianrong Xu China

Torben V. Schroeder Denmark

Chiara Bucciarelli‐Ducci United Kingdom

Marc Dewey Germany

Bettina Baeßler Germany

Douwe E. Atsma Netherlands

Tej D. Azad United States

Daniel S. Hippe United States

Michelle C. Williams

1.9k ×0.5

RNMI

896 ×0.5

CCM

764 ×0.5

SURGE

2.1k ×1.7

PRM

325 ×0.3

Citations per year, relative to Michelle C. Williams Michelle C. Williams (= 1×) peers Daniel S. Hippe

Countries citing papers authored by Michelle C. Williams

Since Specialization

Citations

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

Fields of papers citing papers by Michelle C. Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle C. Williams. 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 Michelle C. Williams. The network helps show where Michelle C. Williams may publish in the future.

Co-authorship network of co-authors of Michelle C. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle C. Williams. A scholar is included among the top collaborators of Michelle C. Williams 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 Michelle C. Williams. Michelle C. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Tomasino, Guadalupe Flores, Caroline Park, Kajetan Grodecki, et al.. (2025). Coronary plaque characteristics quantified by artificial intelligence-enabled plaque analysis: Insights from a multi-ethnic asymptomatic US population. American Journal of Preventive Cardiology. 21. 100929–100929. 1 indexed citations

Cuocolo, Renato, David Bernardini, Daniel Pinto dos Santos, et al.. (2025). AI medical device post-market surveillance regulations: consensus recommendations by the European Society of Radiology. Insights into Imaging. 16(1). 275–275.

Park, Caroline, Guadalupe Flores Tomasino, Kajetan Grodecki, et al.. (2025). AI-quantified epicardial adipose tissue and prediction of future myocardial infarction in patients with cardiometabolic disease: a post-hoc analysis from the SCOT-HEART trial. Cardiovascular Diabetology. 24(1). 403–403.

Williams, Michelle C., Jacek Kwieciński, Jonathan Weir‐McCall, et al.. (2025). Machine learning to predict high-risk coronary artery disease on CT in the SCOT-HEART trial. Open Heart. 12(2). e003162–e003162.

Rasmussen, Laust Dupont, Palle Duun Rohde, Samuel Emil Schmidt, et al.. (2024). Calcium Scoring Improves Clinical Management in Patients With Low Clinical Likelihood of Coronary Artery Disease. JACC. Cardiovascular imaging. 17(6). 625–639. 3 indexed citations

Tzolos, Evangelos, Maaz Syed, Jennifer Nash, et al.. (2024). CT Attenuation of Periaortic Adipose Tissue in Abdominal Aortic Aneurysms. Radiology Cardiothoracic Imaging. 6(1). e230250–e230250. 4 indexed citations

Williams, Michelle C., Jonathan Weir‐McCall, Lauren A. Baldassarre, et al.. (2024). Artificial Intelligence and Machine Learning for Cardiovascular Computed Tomography (CCT): A White Paper of the Society of Cardiovascular Computed Tomography (SCCT). Journal of cardiovascular computed tomography. 18(6). 519–532. 11 indexed citations

Lee, Kuan Ken, David J. Lowe, Rachel O’Brien, et al.. (2023). Troponin in acute chest pain to risk stratify and guide effective use of computed tomography coronary angiography (TARGET-CTCA): a randomised controlled trial. Trials. 24(1). 402–402. 3 indexed citations

Rasmussen, Laust Dupont, Michelle C. Williams, David E. Newby, et al.. (2023). External validation of novel clinical likelihood models to predict obstructive coronary artery disease and prognosis. Open Heart. 10(2). e002457–e002457. 3 indexed citations

10.

Kwieciński, Jacek, Márton Kolossváry, Evangelos Tzolos, et al.. (2023). Latent Coronary Plaque Morphology From Computed Tomography Angiography, Molecular Disease Activity on Positron Emission Tomography, and Clinical Outcomes. Arteriosclerosis Thrombosis and Vascular Biology. 43(7). e279–e290. 9 indexed citations

11.

Williams, Michelle C., et al.. (2023). Role of computed tomography cardiac angiography in acute chest pain syndromes. Heart. 109(18). 1350–1356. 4 indexed citations

12.

Dey, Damini, Rima Arnaout, Sameer Antani, et al.. (2023). Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging. JACC. Cardiovascular imaging. 16(9). 1209–1223. 16 indexed citations

13.

Weir, N., Jonathan Weir‐McCall, Leslee J. Shaw, et al.. (2023). Evaluating Radiation Exposure in Patients with Stable Chest Pain in the SCOT-HEART Trial. Radiology. 308(2). e221963–e221963. 2 indexed citations

14.

Botezatu, Simona, Mohammed N. Meah, Michelle C. Williams, et al.. (2023). Aortic valve perivascular adipose tissue computed tomography attenuation in patients with aortic stenosis. Heart. 110(9). 657–665. 1 indexed citations

15.

Saba, Luca, Christian Loewe, Thomas Weikert, et al.. (2022). State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements—a consensus document by the European Society of Cardiovascular Radiology (ESCR). European Radiology. 33(2). 1063–1087. 31 indexed citations

16.

Wardlaw, Joanna M., Grant Mair, Rüdiger von Kummer, et al.. (2022). Accuracy of Automated Computer-Aided Diagnosis for Stroke Imaging: A Critical Evaluation of Current Evidence. Stroke. 53(7). 2393–2403. 36 indexed citations

17.

Williams, Michelle C., Daniele Massera, Alastair J. Moss, et al.. (2020). Prevalence and clinical implications of valvular calcification on coronary computed tomography angiography. European Heart Journal - Cardiovascular Imaging. 22(3). 262–270. 19 indexed citations

18.

Bularga, Anda, Antti Saraste, Ricardo Fontes‐Carvalho, et al.. (2020). EACVI survey on investigations and imaging modalities in chronic coronary syndromes. European Heart Journal - Cardiovascular Imaging. 22(1). 1–7. 11 indexed citations

19.

Choi, Andrew D., Dustin Thomas, James Lee, et al.. (2020). 2020 SCCT Guideline for Training Cardiology and Radiology Trainees as Independent Practitioners (Level II) and Advanced Practitioners (Level III) in Cardiovascular Computed Tomography: A Statement from the Society of Cardiovascular Computed Tomography. Radiology Cardiothoracic Imaging. 3(1). e200480–e200480. 2 indexed citations

20.

Williams, Michelle C., et al.. (2019). “But I Only Wanted Them to Conform”: A Detailed Look into the Initial Cohort of Girls at the Indiana Reformatory Institution for Women and Girls between 1873 and 1884. ValpoScholar (Valparaiso University). 22(1). 1 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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