Epic AI is reducing administrative burden, and individual features are having a measurable effect.
One example: drafting hospital course notes in discharge summaries by using data already available in the patient's chart.
Our home-grown AF from Sinus AI prediction model published today in #EHJ digital health.
tldr: We reach AUC 0.9 that holds on external validation across continents!💥
@ehj_ed@nyuniversity@nyulangone@DrCardioCon
Read here:
https://t.co/yaCdzLuMQc
New paper out today!
TLDR:
We use special self supervised learning architecture called VICReg, invented by @ylecun to solve the problem of insufficient labeled data
We show that real prevalence of "rare" diseases may be much higher than perceived 😱
https://t.co/JTQB1c5bIs
AI provides a universal framework that leverages data and compute at scale to uncover higher-order patterns
Today, @arcinstitute in collaboration with @nvidia releases Evo 2—a fully open source biological foundation model trained on genomes spanning the entire tree of life 🧵
A multimodal foundation model for medical images from 15 million image-text pairings https://t.co/Xcqu4Xj3pL @NEJM_AI open-source, open-access paper
@hoifungpoon@MSFTResearch
A randomized trial of tailored A.I.-guided ablation of atrial fibrillation vs standard-of-care, anatomical ablation demonstrated superiority of AI guidance
https://t.co/4Q2vJ1vECD
@NatureMedicine
1/n We are excited to announce EchoPrime – the first echocardiography AI model capable of evaluating a full transthoracic echocardiogram study, identify the most relevant videos, and produce a comprehensive interpretation!
Great work lead by @milos_ai, EchoPrime is the largest and most complex #echofirst AI model yet, trained on 10x the data of existing models.
Professor Charged for Operating Multimillion-Dollar Grant Fraud Scheme
Wang allegedly engaged in a scheme to fabricate and falsify scientific data in grant applications made to the NIH on behalf of himself and the biopharmaceutical company.
$SAVA
https://t.co/flzjofbQP6
Prospective RCT of AI-Enhanced ECG for STEMI Activation @NEJM_AI
https://t.co/PnA9VaWT0M
Excellent trial building upon and complementing recent work in @NatureMedicine https://t.co/c73WE1jaCY
Excellent editorial by @RobertAvramMD and @wfearonmd
https://t.co/YKxFathcrc
AI in 🫀
🎉🎉 Our 2nd AI-ECG model dealing with the QT interval, this time for diLQTS ✅ safe prescribing in the outpatient setting.
Reproducible + Standardized nature of ECGs can make them a better input for medical AI models than poorly curated EMR tabular data 📊.
⚡️Just out @JACCJournals⚡️
Prediction of 💊 induced QT prolongation with #AI
💥QTNet - 🆕 architecture for fusing ECG with EHR data
⏱️-dependent prediction from day 0- 180 & external validation
💥day 2 AUC > 0.9
https://t.co/klOzABbNH7
💫@neiljethani
💫@DrCardioCon
💫HaoZhang
Delighted to share ✨Med-Gemini✨ - our new family of multimodal models for medicine unlocking new possibilities for health - https://t.co/7Vqpw33yrK
More accurate multimodal conversations about medical images🩻, surgical videos📽️, genomics🧬, ultra-long health records📚, ECGs🫀 & more with state-of-art performance across multiple benchmarks
More accurate, up-to-date answers to medical questions with advanced reasoning and intelligent use of web-search
Long-context abilities. Summaries or referral letters from long health records, analyses of dozens of long research PDFs & more (1/6)
Excited to share our #echofirst foundation model is now published in @NatureMedicine!
Trained on 1M @CedarsSinai A4C echo-report pairs, EchoCLIP has strong performance on wide range of cardiac diagnostic benchmarks, including LVEF in @StanfordMed videos (MAE 7.1%).
AI-ECG RCT
Alert: pts with ↑ mortality risk
1o endpoint: ↓ all cause mortality
Consent: physicians only
Generalizability limitations, but supporting the value of AI models based on standardized & reproducible inputs (ECG>EMR tabular data) https://t.co/i5kYOmfHi3
Be skeptical of the findings in single-centre RCTs of critically ill patients published in high-impact journals claiming a mortality benefit.
Only 1 out of 16 RCTs were replicated in a multi-centred RCT. https://t.co/1ci8OCvsPx
@First10EM@KirstyChallen@drjohnm@adamcifu
🚨Stunning!🚨
REVERSAL in the decline of heart failure ☠️ in the US 1999-2021
1999-2005 ⬇️ ☠️
2005-2012 ⬇️ ☠️
2012-2019 ⬆️ ☠️
2019-2021 ⬆️⬆️☠️
Age-adjusted HF related ☠️ rates higher in 2021 vs 1999!
WT😱🆘
https://t.co/a7au8TIdJ7
@JAMACardio@FudimMarat
#AI for rare arrhythmia disorders.
Inspired by the work of @ylecun on Self-Supervised Learning, we adapted VICReg, an Energy Based Model to learn deep #EKG representations.
Pre-training with SSL is a promising strategy for rare disease detection.
@nyulangone@nyuniversity
👇