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David Ouyang, MD

@davidouyang.bsky.social

Cardiologist, Data Scientist, AI researcher

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

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

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

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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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

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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