Andreas Coppi
About
Andreas Coppi is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence.
According to data from OpenAlex, Andreas Coppi has authored 27 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cardiology and Cardiovascular Medicine, 7 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Artificial Intelligence. Recurrent topics in Andreas Coppi's work include Machine Learning in Healthcare (5 papers), Cardiac Imaging and Diagnostics (5 papers) and Cardiac Valve Diseases and Treatments (3 papers). Andreas Coppi is often cited by papers focused on Machine Learning in Healthcare (5 papers), Cardiac Imaging and Diagnostics (5 papers) and Cardiac Valve Diseases and Treatments (3 papers). Andreas Coppi collaborates with scholars based in United States, Brazil and United Kingdom. Andreas Coppi's co-authors include Harlan M. Krumholz, Evangelos K. Oikonomou, Rohan Khera, Bobak J. Mortazavi, Lovedeep Singh Dhingra, Wade L. Schulz, Frederick Warner, Arya Aminorroaya, Veer Sangha and Robert L. McNamara and has published in prestigious journals such as Journal of the American College of Cardiology, PLoS ONE and Hypertension.
In The Last Decade
Andreas Coppi
27 papers receiving 397 citations
Hit Papers
Peers
Andreas Coppi
Shorabuddin Syed United States
Chenxi Huang United States
İbrahi̇m Karabayir United States
Andrew Bishara United States
Shu-Xia Li United States
Markus Lingman Sweden
Birju Patel United States
Amjad Ahmed Saudi Arabia
Laura Stevens United States
Citations per year, relative to Andreas Coppi Andreas Coppi (= 1×)
peers
Shorabuddin Syed
Countries citing papers authored by Andreas Coppi
Since
Specialization
Citations
This map shows the geographic impact of Andreas Coppi'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 Andreas Coppi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Coppi more than expected).
Fields of papers citing papers by Andreas Coppi
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Andreas Coppi. 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 Andreas Coppi. The network helps show where Andreas Coppi may publish in the future.
Co-authorship network of co-authors of Andreas Coppi
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Coppi. A scholar is included among the top collaborators of Andreas Coppi 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 Andreas Coppi. Andreas Coppi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Aminorroaya, Arya, Lovedeep Singh Dhingra, Andreas Coppi, et al.. (2025). Development and multinational validation of an ensemble deep learning algorithm for detecting and predicting structural heart disease using noisy single-lead electrocardiograms. European Heart Journal - Digital Health. 6(4). 554–566.
2.
Oikonomou, Evangelos K., Veer Sangha, Andreas Coppi, et al.. (2025). Artificial intelligence-enabled electrocardiography and echocardiography to track preclinical progression of transthyretin amyloid cardiomyopathy. European Heart Journal. 46(37). 3651–3662.
3.
Oikonomou, Evangelos K., Akhil Vaid, Gregory Holste, et al.. (2025). Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study. The Lancet Digital Health. 7(2). e113–e123.
4.
Dhingra, Lovedeep Singh, Arya Aminorroaya, Veer Sangha, et al.. (2025). Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images. Journal of the American College of Cardiology. 85(12). 1302–1313.
5.
Nargesi, Arash Aghajani, Lovedeep Singh Dhingra, Benjamin Rosand, et al.. (2024). Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing. JACC Heart Failure. 13(1). 75–87.
6.
Oikonomou, Evangelos K., Veer Sangha, Lovedeep Singh Dhingra, et al.. (2024). Artificial Intelligence–Enhanced Risk Stratification of Cancer Therapeutics–Related Cardiac Dysfunction Using Electrocardiographic Images. Circulation Cardiovascular Quality and Outcomes. 18(1). e011504–e011504.
7.
Oikonomou, Evangelos K., Gregory Holste, Neal Yuan, et al.. (2024). A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression. JAMA Cardiology. 9(6). 534–534.
8.
Holste, Gregory, Evangelos K. Oikonomou, Bobak J. Mortazavi, et al.. (2023). Severe aortic stenosis detection by deep learning applied to echocardiography. European Heart Journal. 44(43). 4592–4604.
9.
Taylor, Richard A., Aidan Gilson, Wade L. Schulz, et al.. (2023). Computational phenotypes for patients with opioid-related disorders presenting to the emergency department. PLoS ONE. 18(9). e0291572–e0291572.
10.
Khunte, Akshay, Veer Sangha, Evangelos K. Oikonomou, et al.. (2023). Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices. npj Digital Medicine. 6(1). 124–124.
11.
Lind, Margaret L., Alexander J. Robertson, Julio Silva, et al.. (2022). Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case–control analysis. PLoS Medicine. 19(12). e1004136–e1004136.
12.
Lind, Margaret L., Richard Copin, Shane McCarthy, et al.. (2022). Use of Whole-Genome Sequencing to Estimate the Contribution of Immune Evasion and Waning Immunity on Decreasing COVID-19 Vaccine Effectiveness. The Journal of Infectious Diseases. 227(5). 663–674.
13.
Schulz, Wade L., H. P. Young, Andreas Coppi, et al.. (2021). Temporal relationship of computed and structured diagnoses in electronic health record data. BMC Medical Informatics and Decision Making. 21(1). 61–61.
14.
Mori, Makoto, Thomas J S Durant, Chenxi Huang, et al.. (2021). Toward Dynamic Risk Prediction of Outcomes After Coronary Artery Bypass Graft: Improving Risk Prediction With Intraoperative Events Using Gradient Boosting. Circulation Cardiovascular Quality and Outcomes. 14(6). e007363–e007363.
15.
Durant, Thomas J S, R Jean, Chenxi Huang, et al.. (2020). Evaluation of a Risk Stratification Model Using Preoperative and Intraoperative Data for Major Morbidity or Mortality After Cardiac Surgical Treatment. JAMA Network Open. 3(12). e2028361–e2028361.
16.
Durant, Thomas J S, Dustin R. Bunch, Andreas Coppi, et al.. (2019). Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform. Journal of Medical Internet Research. 21(4). e13043–e13043.
17.
Haimovich, Julian S., Arjun K. Venkatesh, Andreas Coppi, et al.. (2017). Discovery of temporal and disease association patterns in condition-specific hospital utilization rates. PLoS ONE. 12(3). e0172049–e0172049.
18.
Dhruva, Sanket S., Chenxi Huang, Erica S. Spatz, et al.. (2017). Heterogeneity in Early Responses in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial). Hypertension. 70(1). 94–102.
19.
Huang, Chenxi, Sanket S. Dhruva, Andreas Coppi, et al.. (2017). Systolic Blood Pressure Response in SPRINT (Systolic Blood Pressure Intervention Trial) and ACCORD (Action to Control Cardiovascular Risk in Diabetes): A Possible Explanation for Discordant Trial Results. Journal of the American Heart Association. 6(11).
20.
Maggioni, Mauro, et al.. (2006). Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6091. 60910I–60910I.
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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