Want to know the state of AI & Cardiology? Our #JACC reviews are for you!
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Pt 1: The field's most comprehensive primer. Every study you should know about in 1 place
Pt 2: Tackling today's evidence, equity, & regulatory challenges
@EricTopol@mattlungrenMD
Excited to finally share the results of our GWAS and multi-trait analyses characterizing the 🧬 genetic architecture of 🫀heart failure, now published in @NatureComms
Thanks to @damrauer and @bvoight28 for their mentorship, and all the contributors!
nature.com/articles/s41467-0…
We got to welcome our new CRADLE teammates to NYC for an on-site! Bringing data scientists like @ChrisMHaggerty to @NYPAdvances and @ColumbiaMed, including our Cath lab & CCU. Started the day with which team could use spaghetti, string, and tape to make the tallest structure 😁
Some news: I’ll be starting Monday as Director of Data Science at NewYork-Presbyterian .. teaming up with @PierreEliasMD to accelerate development and implementation of machine learning in Cardiology across NYP, Columbia, and Cornell hospitals. Really excited for the road ahead..
This means today is my last day at Geisinger after almost 8 years. Tremendously grateful for my time here and the great colleagues I’ve had a chance to work with!
Out today in @JACCJournals, our ValveNet study shows a ML model can detect mod-severe left sided valve disease from ECG. This model is currently running live in our health system daily. Now let me tell you everything wrong with it! A brief 🧵 bit.ly/3boQBRs
How do TTN mutations cause DCM? Haploinsufficiency? Poison Peptides? To date the evidence has been… well, neither. That changes now, with these side-by-side papers in @ScienceTM. 1/3 science.org/doi/10.1126/scit…
If there was an annual award for most popular cardiogenomics gene, FLNC would be firmly in the running to win this year - there have been a few great international FLNC cohorts published, plus its addition to the @TheACMG SF recommendations.
Actual number of affected individuals would likely be higher with result-directed evaluation (and accounting for survival bias). So these findings support the consideration of FLNC LOF as actionable secondary genetic findings.