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ECG Images, Thanks to AI, Can Be Used to Detect Low LVEF

The model also is able to predict which patients who don’t yet have an LVEF < 40% will go on to develop systolic dysfunction.

Arasha nargesiRohan kheraYale cardiovascular data science cards labYale universityMd yale universityCardiovascular data scienceNew havenVeer sanghaYale new haven hospitalDigital medicine

Image-based ECG algorithm improves access to remote care

The new technology hopes to help patients in remote areas across the world, through deep learning

Rohan kheraYale collegeCards labYale cardiovascular data science cards labNational heartNature communications onIndustry newsYale cardiovascular data scienceNature communicationsVeer sanghaBlood instituteNational institutesImage based ecg algorithm improve access to care in remote settings yale universityArtificial intelligenceMachine learningImage analysis

AI-based model can use ECG images to diagnose multiple heart rhythm and conduction disorders

Researchers at the Yale Cardiovascular Data Science (CarDS) Lab have developed an artificial intelligence (AI)-based model for clinical diagnosis that can use electrocardiogram (ECG) images, regardless of format or layout, to diagnose multiple heart rhythm and conduction disorders.

Danielle ellisRohan kheraYale collegeCards labYale cardiovascular data science cards labNature communications onYale cardiovascular data scienceNature communicationsVeer sanghaArtificial intelligenceDeep learning

Can an image-based electrocardiographic algorithm improve access to care in remote settings?

Can an image-based electrocardiographic algorithm improve access to care in remote settings?
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