David Ouyang

6.0k total citations · 6 hit papers
116 papers, 3.1k citations indexed

About

David Ouyang is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, David Ouyang has authored 116 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Cardiology and Cardiovascular Medicine, 37 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Surgery. Recurrent topics in David Ouyang's work include Cardiovascular Function and Risk Factors (31 papers), Cardiac Imaging and Diagnostics (28 papers) and ECG Monitoring and Analysis (15 papers). David Ouyang is often cited by papers focused on Cardiovascular Function and Risk Factors (31 papers), Cardiac Imaging and Diagnostics (28 papers) and ECG Monitoring and Analysis (15 papers). David Ouyang collaborates with scholars based in United States, Canada and Taiwan. David Ouyang's co-authors include James Zou, Bryan He, Neal Yuan, Euan A. Ashley, David Liang, Robert A. Harrington, Joseph E. Ebinger, Amirata Ghorbani, Jonathan H. Chen and Susan Cheng and has published in prestigious journals such as Nature, Circulation and Nature Medicine.

In The Last Decade

David Ouyang

102 papers receiving 3.1k citations

Hit Papers

5 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.

Video-based AI for beat-to-beat assessment of cardiac function

2020 519 citations David Ouyang, Bryan He et al. Nature profile →
Deep learning interpretation of echocardiograms

2020 288 citations David Ouyang, Bryan He et al. npj Digital Medicine profile →
How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals

2021 275 citations David Ouyang, James Zou et al. profile →
Blinded, randomized trial of sonographer versus AI cardiac function assessment

2023 116 citations Bryan He, Alan C. Kwan et al. Nature profile →
Sex Differences in Association of Physical Activity With All-Cause and Cardiovascular Mortality

2024 85 citations Alan C. Kwan, David Ouyang et al. profile →
Vision–language foundation model for echocardiogram interpretation

2024 68 citations Neal Yuan, David Ouyang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Ouyang United States	28	1.2k	1.0k	526	394	323	116	3.1k
Elena Bignami Italy	35	1.5k 1.3×	583 0.6×	739 1.4×	362 0.9×	359 1.1×	180	4.4k
Patrick Tighe United States	26	539 0.5×	313 0.3×	483 0.9×	871 2.2×	181 0.6×	123	3.2k
William B. Gormley United States	36	358 0.3×	443 0.4×	271 0.5×	173 0.4×	369 1.1×	134	3.8k
Joseph E. Ebinger United States	24	1.0k 0.9×	517 0.5×	137 0.3×	150 0.4×	164 0.5×	88	2.6k
Chris Sidey‐Gibbons United States	28	221 0.2×	364 0.4×	269 0.5×	386 1.0×	128 0.4×	102	3.0k
Vijaya B. Kolachalama United States	28	289 0.2×	405 0.4×	236 0.4×	453 1.1×	274 0.8×	106	2.3k
Zachi I. Attia United States	32	4.3k 3.7×	994 1.0×	903 1.7×	590 1.5×	606 1.9×	172	6.0k
Myura Nagendran United Kingdom	23	442 0.4×	367 0.4×	353 0.7×	236 0.6×	374 1.2×	62	2.5k
Feng Xie United States	30	418 0.4×	649 0.6×	79 0.2×	250 0.6×	796 2.5×	147	2.9k
Suraj Kapa United States	41	5.6k 4.8×	878 0.9×	496 0.9×	354 0.9×	546 1.7×	216	7.3k

Countries citing papers authored by David Ouyang

Since Specialization

Citations

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

Fields of papers citing papers by David Ouyang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Ouyang

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

Chiu, I-Min, Neal Yuan, Tien‐Yu Chen, et al.. (2025). Comprehensive echocardiogram evaluation with view primed vision language AI. Nature. 650(8103). 970–977. 1 indexed citations

Sahashi, Yuki, Fatemeh Amrollahi, Hirsh D. Trivedi, et al.. (2025). Opportunistic Screening of Chronic Liver Disease with Deep-Learning–Enhanced Echocardiography. NEJM AI. 2(3). 4 indexed citations

Bandyopadhyay, Sabyasachi, Rishi Trivedi, Jasmine Hughes, et al.. (2025). Deep Learning–Based Continuous QT Monitoring to Identify High-Risk Prolongation Events After Class III Antiarrhythmic Initiation. Circulation. 153(1). 35–46.

Hughes, J. Weston, Sulaiman Somani, Pierre Elias, et al.. (2024). Simple models vs. deep learning in detecting low ejection fraction from the electrocardiogram. European Heart Journal - Digital Health. 5(4). 427–434. 2 indexed citations

Zou, James, et al.. (2024). Detection of cardiac amyloidosis using machine learning on routine echocardiographic measurements. Open Heart. 11(2). e002884–e002884. 1 indexed citations

Bowdish, Michael E., et al.. (2024). Deep learning for transesophageal echocardiography view classification. Scientific Reports. 14(1). 11–11. 15 indexed citations

Zhang, Huan, J. Weston Hughes, Albert J. Rogers, et al.. (2024). Serum Potassium Monitoring Using AI-Enabled Smartwatch Electrocardiograms. JACC. Clinical electrophysiology. 10(12). 2644–2654. 10 indexed citations

Kwan, Alan C., et al.. (2024). Machine Learning and Bias in Medical Imaging: Opportunities and Challenges. Circulation Cardiovascular Imaging. 17(2). e015495–e015495. 24 indexed citations

Yuan, Neal, Nathan R. Stein, Grant Duffy, et al.. (2024). Deep learning evaluation of echocardiograms to identify occult atrial fibrillation. npj Digital Medicine. 7(1). 96–96. 8 indexed citations

10.

Kwan, Alan C., Ernest W. Chang, François Haddad, et al.. (2024). Deep Learning-Derived Myocardial Strain. JACC. Cardiovascular imaging. 17(7). 715–725. 23 indexed citations

11.

Duffy, Grant, et al.. (2024). High-Throughput Deep Learning Detection of Mitral Regurgitation. Circulation. 150(12). 923–933. 14 indexed citations

12.

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. 57 indexed citations

13.

Holmström, Lauri, Zijun Zhang, David Ouyang, et al.. (2023). Artificial Intelligence in Ventricular Arrhythmias and Sudden Death. Arrhythmia & Electrophysiology Review. 12. e17–e17. 7 indexed citations

14.

Sangha, Veer, Arash Aghajani Nargesi, Lovedeep Singh Dhingra, et al.. (2023). Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images. Circulation. 148(9). 765–777. 63 indexed citations

15.

Soto, Jessica Torres, J. Weston Hughes, Pablo Sanchez, et al.. (2022). Multimodal deep learning enhances diagnostic precision in left ventricular hypertrophy. European Heart Journal - Digital Health. 3(3). 380–389. 40 indexed citations

16.

Popescu, Dan M., Julie K. Shade, Konstantinos N. Aronis, et al.. (2022). Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart. Nature Cardiovascular Research. 1(4). 334–343. 58 indexed citations

17.

Duffy, Grant, Shoa L. Clarke, Bryan He, et al.. (2022). Confounders mediate AI prediction of demographics in medical imaging. npj Digital Medicine. 5(1). 188–188. 27 indexed citations

18.

Kwan, Alan C., Joseph E. Ebinger, Janet Wei, et al.. (2022). Apparent risks of postural orthostatic tachycardia syndrome diagnoses after COVID-19 vaccination and SARS-Cov-2 Infection. Nature Cardiovascular Research. 1(12). 1187–1194. 43 indexed citations

19.

Kwan, Alan C., David Ouyang, Chike C. Nwabuo, et al.. (2022). Cardiac microstructural alterations measured by echocardiography identify sex-specific risk for heart failure. Heart. 108(22). 1800–1806. 4 indexed citations

20.

Ouyang, David, Gunsagar S. Gulati, Richard Ha, & Dipanjan Banerjee. (2018). Incidence of temporary mechanical circulatory support before heart transplantation and impact on post-transplant outcomes. The Journal of Heart and Lung Transplantation. 37(9). 1060–1066. 45 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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