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this really clarifies things

#diffusion #melts #brains

Does combining clinical, genetic & ECG-based #AI risk tools to predict incident atrial fibrillation lead to more bang for your buck? Find out in our new preprint where we developed the comprehensive Predict-AF3 model to estimate incident AF risk. A 🧵 medrxiv.org/content/10.110…

Is the spleen, a hematopoietic organ, involved in coronary artery disease❤️? Our new study, led by Meghana & co-supervised with Pradeep Natarajan, used deep learning to reveal non-invasive insights into spleen pathologies and their shared🧬basis with CAD. medrxiv.org/content/10.110…

If you’re at European Society of Cardiology #ESC2024 #ESCCongress2024 Check out 2 presentations from our group: Aug 30 14:41 - ECG artificial intelligence to detect prevalent CAD Shino Kany Aug 31 10:00 - CAD polygenic risk score and outcomes after coronary angiography Kelvin Supriami

These diffused ECGs do not exist! #diffusion #Generative #ECG

Can ECG #AI predict who will develop #afib after stroke (eg, to prioritize for ILR)? Yes! New in CircEP our ML4H ECG #AI #afib risk model discriminates cardioembolic stroke (>> clinical factors) & stratifies risk of new #afib after stroke: bit.ly/3TT5jmz

What does a 1-parameter autoencoder of cardiac MRIs learn? If you use that 1 number to parameterize a circle you learn the heart beat, if not, you learn the exposure value of the image -- It depends on the inductive bias! Deets in: journals.sagepub.com/doi/10.1177/11…

Just how many diseases can you identify with a good old 12-lead #ECG? NEW npj Digital Medicine, co-led w/ Sam Freesun Friedman, RVpacing & xwang, we use an autoencoder to map ECG to phenome, finding associations btwn ECG & >600 conditions Broad Institute ML4H Mass General Heart LINK⬇️