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David Ouyang, MD

@davidouyang.bsky.social
125 followers 58 following 23 posts

Cardiologist, Data Scientist, AI researcher

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David Ouyang, MD @davidouyang.bsky.social · 01/12/2025
Amazing and congrats!
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David Ouyang, MD @davidouyang.bsky.social · 17/11/2025
Paper: nature.com/articles/s41... Code: github.com/echonet/Echo... Trial: clinicaltrials.gov/study/NCT072... Blog: substack.com/home/post/p-... Press: divisionofresearch.kaiserpermanente.org/large-ai-int...
nature.com
Comprehensive echocardiogram evaluation with view primed vision language AI - Nature
Nature - Comprehensive echocardiogram evaluation with view primed vision language AI
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David Ouyang, MD @davidouyang.bsky.social · 17/11/2025
EchoPrime is a contrastive vision-language model. Trained on over 12M video-repprt pairs, it learns the relationship between what cardiologists write and what the ultrasound images show. If you feed it a video or echo reports, it can find similar historical studies that match those concepts.
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David Ouyang, MD @davidouyang.bsky.social · 17/11/2025
EchoPrime is the culmination of a long roadmap for AI echo. Substantial time and effort was put into curating the largest existing echocardiography database. EchoPrime is trained on 1000x the data of EchoNet-Dynamic, our first model for AI-LVEF, and 10x the data of existing AI echo models.
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David Ouyang, MD @davidouyang.bsky.social · 17/11/2025
We are excited to announce EchoPrime is published in Nature. EchoPrime is the first echocardiography AI model capable of evaluating a full transthoracic echocardiogram study, identify the most relevant videos, and produce a comprehensive interpretation!
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Reposted by David Ouyang, MD
Eric Topol @erictopol.bsky.social · 12/11/2025
Echocardiography is one of the most complex medical image sets to analyze, with multiple views + cardiac motion. A new @nature.com paper shows how A.I. can do that and provide accurate reports @davidouyang.bsky.social nature.com/articles/s41...
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David Ouyang, MD @davidouyang.bsky.social · 04/05/2025
The deep learning pipeline was more reproducible and had better concordance with guidelines. And it’s open source! Preprint: medrxiv.org/content/10.1... Code: github.com/echonet/dias...
medrxiv.org
Automated Deep Learning Pipeline for Characterizing Left Ventricular Diastolic Function
Introduction: Left ventricular diastolic dysfunction (LVDD) is most commonly evaluated by echocardiography. However, without a sole identifying metric, LVDD is assessed by a diagnostic algorithm relyi...
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David Ouyang, MD @davidouyang.bsky.social · 04/05/2025
Victoria developed a fully automated pipeline that processes an entire #echofirst study, view classifies important views, rejects low quality images, derives measurements from each image, and uses the @ase360.bsky.social algorithm to assess diastolic function.
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David Ouyang, MD @davidouyang.bsky.social · 04/05/2025
Diastolic function underpins many cardiac conditions, including HFpEF, however #echofirst assessment is complex. @ase360.bsky.social expert guidelines integrate many elements for comprehensive assessment, however its complexity lead to missingness and inconsistency in clinical practice.
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David Ouyang, MD @davidouyang.bsky.social · 04/05/2025
Congratulations to Sarnoff Fellow Victoria Yuan on her new preprint 'Automated Deep Learning Pipeline for Characterizing Left Ventricular Diastolic Function'!
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David Ouyang, MD @davidouyang.bsky.social · 25/03/2025
n/n Congrats Christina! Preprint: medrxiv.org/content/10.1... Github: github.com/echonet/AR
medrxiv.org
Automated Aortic Regurgitation Detection and Quantification: A Deep Learning Approach Using Multi-View Echocardiography
Abstract Background: Accurate evaluation of aortic regurgitation (AR) severity is necessary for early detection and chronic disease management. AR is most commonly assessed by Doppler echocardiography...
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David Ouyang, MD @davidouyang.bsky.social · 25/03/2025
3/n Without additional prompting, our #echofirst model naturally gravitates towards the vena contracta in color Doppler videos to assess AR severity.
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David Ouyang, MD @davidouyang.bsky.social · 25/03/2025
2/n Accurate assessment of AR severity and sequalae is critical for surveillance and timing of surgery. Using over 40k studies from @smidtheart.bsky.social and validated on 1.5k studies from @stanforddeptmed.bsky.social, we show that AI can accurately assess AR severity across a range of patients.
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David Ouyang, MD @davidouyang.bsky.social · 25/03/2025
1/n Excited to announce work by Dr. @BinderRodriguez from @MedUni_Wien on the AI automated assessment of Aortic Regurgitation (AR) on #echofirst using 59,500 videos from @smidtheart.bsky.social. Lead by Dr. Bob Siegel.
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David Ouyang, MD @davidouyang.bsky.social · 20/03/2025
5/n Preprint: medrxiv.org/content/10.1... GitHub: github.com/echonet/meas... Demo: On Github.
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David Ouyang, MD @davidouyang.bsky.social · 20/03/2025
4/n Combined with EchoPrime, which enables automated structured reporting, with EchoNet-Measurements, which enables automated measurements, we envision truly automated comprehensive echocardiography. Access to #POCUS and #echofirst improves accuracy and access to care. x.com/David_Ouyang...
x.com
David Ouyang, MD on X: "1/n We are excited to announce EchoPrime – the first echocardiography AI model capable of evaluating a full transthoracic echocardiogram study, identify the most relevant videos, and produce a comprehensive interpretation! Great work lead by @milos_ai, EchoPrime is the largest https://t.co/dPTK9cXO5Y" / X
1/n We are excited to announce EchoPrime – the first echocardiography AI model capable of evaluating a full transthoracic echocardiogram study, identify the most relevant videos, and produce a comprehensive interpretation! Great work lead by @milos_ai, EchoPrime is the largest https://t.co/dPTK9cXO5Y
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David Ouyang, MD @davidouyang.bsky.social · 20/03/2025
3/n Across a wide range of image quality, patient characteristics, and study types, EchoNet-Measurements perform well, improving upon sonographers' and cardiologists' precision.
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David Ouyang, MD @davidouyang.bsky.social · 20/03/2025
2/n Lead by Yuki Sahashi, EchoNet-Measurements provide automated annotations for the 18 most common #echofirst (both B mode and Doppler) measurements. Excellent performance in test cohorts (overall R2 of 0.967 in the held-out CSMC dataset and 0.987 in the SHC dataset)
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David Ouyang, MD @davidouyang.bsky.social · 20/03/2025
1/n We are thrilled to present EchoNet-Measurements, an open source, comprehensive AI platform for automated #echofirst measurements. Using more than 1,414,709 annotations from 155,215 studies from 78,037 patients for training, this is the most comprehensive #echofirst segmentation model.
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David Ouyang, MD @davidouyang.bsky.social · 18/03/2025
media.tenor.com
a cartoon of a chef with a needle in his mouth is playing at 4:32
ALT: a cartoon of a chef with a needle in his mouth is playing at 4:32
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David Ouyang, MD @davidouyang.bsky.social · 18/03/2025
My favorite feature is if you have multiple calendars, it’s put side by side
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Reposted by David Ouyang, MD
NEJM AI @ai.nejm.org · 07/03/2025
A new article highlights an #AI algorithm that screens for chronic liver diseases in patients undergoing transthoracic echocardiography studies, using standard subcostal images routinely obtained to evaluate the inferior vena cava. Full article: nejm.ai/3XJuPNl #MedSky #MLSky
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David Ouyang, MD @davidouyang.bsky.social · 07/03/2025
This model is trained on cases and controls matched by wall thickness, and is able to accurately identify who has LVOT obstruction. Strong performance validated at two sites. Talk to us at #acc25 if any questions! Preprint: medrxiv.org/content/10.1... Github: github.com/echonet/obst...
medrxiv.org
Detection of Left Ventricular Outflow Obstruction from Standard B-Mode Echocardiogram Videos using Deep Learning
Abstract Introduction Hypertrophic cardiomyopathy (HCM) affects 20 million individuals globally, with increased risk of sudden death and heart failure. While cardiac myosin inhibitors show great promi...
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David Ouyang, MD @davidouyang.bsky.social · 07/03/2025
New preprint by @SarnoffCardio and @dgsomucla Victoria Yuan: There are new therapies for obstructive HCM, however obstruction is frequently missed. Extra #echofirst work is required to eval for obstruction. We develop an AI model on standard A4C videos to identify patients w/ obstruction.
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David Ouyang, MD @davidouyang.bsky.social · 05/03/2025
Consistency - one of the most useful heuristics of whether a medical AI model is good or not. I've noticed that AI models trained on small datasets tend to jitter - jumping a lot from frame to frame - while robust models tend to have consistent measurements across the entire video. Coming soon...
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Reposted by David Ouyang, MD
NEJM AI @ai.nejm.org · 28/02/2025
Original Article: Development and Evaluation of a Model to Manage Patient Portal Messages nejm.ai/3XmIx8m Original Article: Opportunistic Screening of Chronic Liver Disease with Deep-Learning–Enhanced Echocardiography nejm.ai/3XJuPNl
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Reposted by David Ouyang, MD
alanckwan.bsky.social @alanckwan.bsky.social · 27/02/2025
Hey! I'm new here, but into science. Here's a paper that we just published (today) which uses deep learning on echocardiography to identify liver disease on subcostal views. I'm hoping that this type of cross-organ / somewhat multi-modal approaches inspires people! ai.nejm.org/stoken/defau...
urldefense.com
Opportunistic Screening of Chronic Liver Disease with Deep-Learning–Enhanced Echocardiography
Chronic liver disease (CLD) affects more than 1.5 billion adults, most of whom are asymptomatic and undiagnosed. Echocardiography is broadly performed and visualizes the liver, but this information...
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