Andrew Lin

2.4k total citations
72 papers, 1.1k citations indexed

About

Andrew Lin is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Andrew Lin has authored 72 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Cardiology and Cardiovascular Medicine, 45 papers in Radiology, Nuclear Medicine and Imaging and 21 papers in Surgery. Recurrent topics in Andrew Lin's work include Cardiac Imaging and Diagnostics (44 papers), Cardiovascular Disease and Adiposity (35 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (11 papers). Andrew Lin is often cited by papers focused on Cardiac Imaging and Diagnostics (44 papers), Cardiovascular Disease and Adiposity (35 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (11 papers). Andrew Lin collaborates with scholars based in United States, Australia and United Kingdom. Andrew Lin's co-authors include Damini Dey, Nitesh Nerlekar, Stephen J. Nicholls, Dennis T. L. Wong, Jeremy Yuvaraj, Piotr J. Slomka, Márton Kolossváry, Pál Maurovich‐Horvat, Dennis Wong and Sebastien Cadet and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and Scientific Reports.

In The Last Decade

Andrew Lin

65 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew Lin United States 20 744 591 420 187 83 72 1.1k
Pedro de Araújo Gonçalves Portugal 15 910 1.2× 586 1.0× 443 1.1× 103 0.6× 136 1.6× 148 1.3k
Edoardo Conte Italy 24 913 1.2× 1.1k 1.9× 458 1.1× 485 2.6× 189 2.3× 137 1.7k
Bjørnar Grenne Norway 18 1.3k 1.7× 869 1.5× 320 0.8× 115 0.6× 68 0.8× 66 1.5k
Diego Medvedofsky United States 22 1.3k 1.7× 569 1.0× 363 0.9× 187 1.0× 342 4.1× 71 1.6k
Faraz Pathan Australia 16 961 1.3× 546 0.9× 179 0.4× 65 0.3× 105 1.3× 67 1.1k
Matthew Lumley United Kingdom 14 541 0.7× 318 0.5× 364 0.9× 187 1.0× 33 0.4× 31 860
Júlia Karády Hungary 17 517 0.7× 656 1.1× 345 0.8× 269 1.4× 134 1.6× 59 993
Alaa Mabrouk Salem Omar United States 11 844 1.1× 610 1.0× 176 0.4× 116 0.6× 91 1.1× 55 1.2k
Kristian Altern Øvrehus Denmark 17 524 0.7× 835 1.4× 529 1.3× 246 1.3× 134 1.6× 55 1.1k
Márton Tokodi Hungary 22 812 1.1× 233 0.4× 159 0.4× 77 0.4× 349 4.2× 73 1.0k

Countries citing papers authored by Andrew Lin

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Lin

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

All Works

20 of 20 papers shown
1.
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
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Cheng, Kevin, Jeremy Yuvaraj, Stephen J. Nicholls, et al.. (2025). Effect of statin therapy on coronary inflammation assessed by pericoronary adipose tissue computed tomography attenuation. European Heart Journal - Cardiovascular Imaging. 26(5). 784–793. 3 indexed citations
5.
Zhao, Yanling, Andrew Lin, Yuji Kaku, et al.. (2024). Outcomes Comparison of Extracorporeal Membrane Oxygenation Support for Cardiogenic Shock with Acute Decompensated Heart Failure versus Acute Myocardial Infarction. The Journal of Heart and Lung Transplantation. 43(4). S278–S279. 1 indexed citations
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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
8.
Pang, Stephen C., et al.. (2024). Coronary Artery Calcium Density And Risk Of Cardiovascular Events: A Systematic Review And Meta-analysis. Journal of cardiovascular computed tomography. 18(4). S54–S54.
9.
Kolossváry, Márton, Andrew Lin, Jacek Kwieciński, et al.. (2024). Coronary Plaque Radiomic Phenotypes Predict Fatal or Nonfatal Myocardial Infarction. JACC. Cardiovascular imaging. 18(3). 308–319. 2 indexed citations
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Khan, Muhammad Arif, G. Glenn Lipscomb, Andrew Lin, et al.. (2023). Performance evaluation and model of spacesuit cooling by hydrophobic hollow fiber-membrane based water evaporation through pores. Journal of Membrane Science. 673. 121497–121497. 11 indexed citations
12.
Szilveszter, Bálint, Melinda Boussoussou, Milán Vecsey-Nagy, et al.. (2023). Impact of virtual monoenergetic levels on coronary plaque volume components using photon-counting computed tomography. European Radiology. 33(12). 8528–8539. 25 indexed citations
13.
Patel, Kush, Andrew Lin, Niraj Kumar, et al.. (2023). Influence of cusp morphology and sex on quantitative valve composition in severe aortic stenosis. European Heart Journal - Cardiovascular Imaging. 24(12). 1653–1660. 8 indexed citations
14.
Boussoussou, Melinda, Bálint Szilveszter, Judit Simon, et al.. (2022). The effect of patient and imaging characteristics on coronary CT angiography assessed pericoronary adipose tissue attenuation and gradient. Journal of cardiovascular computed tomography. 17(1). 34–42. 13 indexed citations
15.
Lin, Andrew, Márton Kolossváry, Manish Motwani, et al.. (2021). Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease. Radiology Cardiothoracic Imaging. 3(1). e200512–e200512. 60 indexed citations
16.
Yuvaraj, Jeremy, D. William Cameron, Jordan Andrews, et al.. (2021). Coronary computed tomography angiography-based assessment of vascular inflammation in patients with obstructive sleep apnoea and coronary artery disease. Cardiovascular Diagnosis and Therapy. 12(1). 123–134. 4 indexed citations
17.
Han, Donghee, Andrew Lin, Heidi Gransar, Damini Dey, & Daniel S. Berman. (2020). Influence of Coronary Artery Calcium Score on Computed Tomography–Derived Fractional Flow Reserve. JACC. Cardiovascular imaging. 14(3). 702–703. 8 indexed citations
18.
Lin, Andrew, Nitesh Nerlekar, Jeremy Yuvaraj, et al.. (2020). PERICORONARY ADIPOSE TISSUE COMPUTED TOMOGRAPHY ATTENUATION IN DIFFERENT STAGES OF CORONARY ARTERY DISEASE: A CROSS-SECTIONAL STUDY. Journal of the American College of Cardiology. 75(11). 1718–1718. 2 indexed citations
19.
Morgan, Meredith W., et al.. (2016). Definitions of Obstetric and Gynecologic Hospitalists. Obstetrics and Gynecology. 127(2). 393–397. 5 indexed citations
20.
Lin, Andrew, et al.. (2016). Abstract 11330: E/e’ is a Powerful Predictor of Survival After a First-Ever Non-ST Elevation Myocardial Infarction. Circulation. 134(suppl_1). 3 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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