David Ouyang, MD
@davidouyang.bsky.social
Cardiologist, Data Scientist, AI researcher
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.
If you feed it a video or echo reports, it can find similar historical studies that match those concepts.
November 17, 2025 at 2:41 AM
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.
If you feed it a video or echo reports, it can find similar historical studies that match those concepts.
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!
November 17, 2025 at 2:38 AM
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!
Congratulations to Sarnoff Fellow Victoria Yuan on her new preprint 'Automated Deep Learning Pipeline for Characterizing Left Ventricular Diastolic Function'!
May 4, 2025 at 4:12 AM
Congratulations to Sarnoff Fellow Victoria Yuan on her new preprint 'Automated Deep Learning Pipeline for Characterizing Left Ventricular Diastolic Function'!
March 20, 2025 at 10:35 PM
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.
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.
March 20, 2025 at 10:33 PM
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.
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.
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...
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...
March 5, 2025 at 12:04 AM
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...
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...