David Ouyang

Research Scientist and Cardiologist, Kaiser Permanente Division of Research
Assistant Professor, Cedars-Sinai Medical Center
david.ouyang@kp.org
[CV]

Our mission is to improve cardiovascular diagnosis and disease detection using computer vision and artificial intelligence. Our group works on applications of deep learning, computer vision, and the statistical analysis of large datasets within cardiovascular medicine. We focus on AI model development (see section 'Precision Phenotyping'), AI model understanding (see section 'Interpretable Medical AI'), and AI model deployment and implementation (see section 'AI Clinical Trials'). We are interested in all forms of cardiovascular data, including ECG, MRI, radiological imaging, and particicularly interested in novel insights from pre-existing data.Our work has been published in Nature, Nature Medicine, NEJM AI, Circulation, JAMA Cardiology, EHJ, and other scientific venues.

I am a cardiologist and researcher in the Santa Clara Homestead Medical Center and Division of Research at Kaiser Permanente Northern California. I am also an adjunct Assistant Professor at the Smidt Heart Institute at Cedars-Sinai. As a physician-scientist and statistician with focus on cardiology and imaging, I majored in statistics at Rice University, obtained my MD at UCSF, and received post-graduate medical education in internal medicine, cardiology, and a postdoc in computer science and biomedical data science at Stanford University. I am also a Deputy Editor at NEJM AI

Our group works on multi-modal datasets, leveraging EHR, ECG, echo, and MRI data for a broad perspective on cardiovascular disease. Our lab members bring expertise from a wide range of backgrounds ranging from physics, mechanical engineering, computer science to cardiology, anesthesia, and internal medicine.

The best part of the job are the poeple I get work with. I have the good fortune of working with a great group of motivated, talented, and creative individuals from a wide range of backgrounds.

Members of the lab include:

Kai Christensen, Data Scientist

Milos Vukadinovic, UCLA Bioengineering PhD Student

Yuki Sahashi, Postdoctoral Fellow, Electrophysiologist

Justin Rhee, Brown University Medical Student

Victoria Yuan, UCLA Medical Student, Sarnoff Fellow

Meenal Rawlani, Data Scientist

Hirotaka Ieki, Postdoctoral Fellow, Cardiologist

David Choi, Data Scientist

Rishi Truvedi, Cardiology Fellow

Dhawal Modi, Data Scientist

Alumni of the lab include:

Christina Binder-Rodriguez, Cardiologist, Medical University of Vienna

Yu Sun, Assistant Professor, ECE, Johns Hopkins University

Grant Duffy, Data Scientist, Meta

I-Min Chiu, Data Scientist, Apple

Weston Hughes, Data Scientist, Columbia

Ting Qi, Software Engineer, Amazon

John Theurer, Software Engineer, Zither Labs

Amey Vrudhula, Internal Medicine Resident, Stanford

Gauri Renjith, Undergraduate, UCSD

Ishan Jain, Undergraduate, UCSB

If you're interested in improving cardiovascular imaging and cardiovascular care, please email me!

Precision Phenotyping

• Ouyang D, He B, Ghorbani A, Langlotz CP, Heidenreich PA, Harrington RA, Liang DH, Ashley EA, Zou JY. “Video-based artificial intelligence for beat-to-beat assessment of cardiac function ” Nature.
• Duffy G*, Cheng PP*, Yuan*,He B, Kwan AC, Shun-Shin MJ, Alexander KM, Ebinger J, Lungren MP, Rader F, Liang DH, Schnittger I, Ashley EA, Zou JY, Patel J, Witteles R, Cheng S, Ouyang D. “High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning.” JAMA Cardiology
• Christensen M, Vukadinovic M, Yuan N, Ouyang D. “Vision–language foundation model for echocardiogram interpretation”. Nature Medicine
• Sahashi Y, Vukadinovic M, Amrollahi F, Trivedi H, Rhee J, Chen JH, Cheng S, Ouyang D, Kwan AC. “Opportunistic Screening of Chronic Liver Disease with Deep Learning Enhanced Echocardiography”. NEJM AI

AI Clinical Trials and Deployment

• He B, Kwan AC, Cho JH, Yuan N, Pollick C, Shiota T, Ebinger J. Bello NA, Wei J, Josan K, Duffy G, Jujjavarapu M, Siegel R, Cheng S, Zou JY, Ouyang D. “EchoNet-RCT: Blinded, Randomized Controlled Trial of Sonographer vs. Artificial Intelligence Assessment of Cardiac Function.” Nature
• Wu E, Wu K, Daneshjou R, Ouyang D, Ho D, Zou JY. “How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals.” Nature Medicine
• Ongoing , “Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases (EchoNet-Screening).”

Foundation Models in Cardiovascular Medicine

• Vukadinovic M, Tang X, Yuan N, Cheng P, Li D, Cheng S, He B, Ouyang D. “EchoPrime: A Multi-Video View-Informed Vision-Language Model for Comprehensive Echocardiography Interpretation.” Preprint
• Christensen K, Vukadinovic M, Yuan N, Ouyang D. “Vision-language foundation model for echocardiogram interpretation” Nature Medicine
• He B, Vukadinovic M, Duffy G, Zou JY, Ouyang D. “Multi-Modal Contrastive Learning across Cardiac Diagnostics.” Preprint

Interpreting Medical AI

• Gorbhani A, Ouyang D, Abid A, He B, Chen JH, Harrington RA, Liang DH, Ashley EA, Zou JY. “Deep Learning Interpretation of Echocardiograms.” npj Digital Medicine.
• Duffy G, Clarke SL, Christensen M, He B, Yuan N, Cheng S, Ouyang D “Confounders mediate AI prediction of demographics in medical imaging” npj Digital Medicine. ”
• Weston HJ, Yuan N, He B, Ouyang J, Ebinger J, Botting P, Lee J, Theurer J, Tooley JE, Neiman K, Lungren MP, Liang D, Schnittger I, Harrington B, Chen JH, Ashley EA, Cheng S, Ouyang D, Zou JY. “Deep learning evaluation of biomarkers from echocardiogram videos.” EbioMedicine
• Vrudhula A, Hughes JW, Yuan N, Ouyang D. “The Impact of Task Set-up in Algorithm Design: Regression versus Classification.” New England Journal of Medicine AI ”

AI Echocardiography

• Vrudhula A, Duffy D, Vukadinovic M, Liang D, Cheng S, Ouyang D. “High Throughput Deep Learning Detection of Mitral Regurgitation.” Circulation
• Vrudhula A, Vukadinovic M, Haeffle C, Kwan AC, Berman D, Liang D, Siegel R, Cheng S, Ouyang D. “Automated Deep Learning Phenotyping of Tricuspid Regurgitation in Echocardiography.” JAMA Cardiology
• Holste G, Oikonomou E, ... , Khera R. “Severe aortic stenosis detection by deep learning applied to echocardiography.” European Heart Journal
• Kwan AC, Chang EW, Jain I, Theurer J, Tang X, Francisco, ..., Ouyang D. “Deep Learning-derived Myocardial Strain.” JACC: Cardiovascular Imaging
• He B, Dash D, Duanmu YY, Tan TX, Ouyang D, Zou JY. “AI-enabled assessment of cardiac function and video quality in emergency department point-of-care echocardiograms.” The Journal of Emergency Medicine February 2, 2024
• Reddy CD, Lopez L, Ouyang D, Zou JY, He B. “Video-based deep learning for automated assessment of left ventricular ejection fraction in pediatric patients.” Journal of the American Society of Echocardiography

Healthcare Data Science

• Ouyang D, Gulati G, Ha R, Banerjee D. “Incidence of Temporary Mechanical Circulatory Support Prior to Heart Transplantation and Impact on Post-Transplant Outcomes.” Journal of Heart and Lung Transplantation
• Ouyang D, Tisdale R, Cheng P, Chi J, Ashley EA, Chen JH. “Acetaminophen or Tylenol? A Retrospective Analysis of Medication Digital Communication Practices.” Journal of General Internal Medicine
• Ouyang D, Chen J, Krishnan G, Hom J, Witteles R, Chi J. “Patient Outcomes When Housestaff Exceed Eighty Hours per Week.” American Journal of Medicine.
• Ouyang D, Chen J, Hom J, Chi J. “How Much Time Do Internal Medicine Residents Spend on the Computer?: An Electronic Audit of an Inpatient Service.” JAMA Internal Medicine.,
• Ouyang D, I El-Sayed, SS Yom. National Trends in Surgery for Sinonasal Malignancy and the Effect of Hospital Volume on Short-Term Outcome. Laryngoscope.

A complete list of publications is available at Google Scholar