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🚨 New CardioTechX Journal Club Episode 🚨 We're diving into PanEcho: a groundbreaking #AI tool for echocardiography interpretation using multi-task deep learning. 🌟 #CardioTwitter #MedEd #echofirst #Cardiology #ArtificialInteligence #MedicalResearch

🚨 Discover DeepSeek-V3: The open-source rival to ChatGPT🚨 Experience DeepSeek V3's capabilities for free here: deepseek.com #DeepSeek #ChatGPT #OpenSourceAI #CardioTwitter #AI #Cardiology #MedEd #MedTwitter #MedicalResearch

🚨 New CardioTechX Journal Club Episode 🚨 We’re highlighting a groundbreaking #AI-ECG model that predicts future heart failure risk from an ECG image—validated across multinational cohorts! Discover how #ArtificialIntelligence is redefining digital biomarkers and #HeartFailure

🚨 New CardioTechX Journal Club Episode🚨 We’re spotlighting the FLASH trial: an #AI-based quantitative coronary angiography approach that matches #OCT in PCI outcomes—all while streamlining stent sizing and deployment. #CardioTwitter #MedEd #Cardiology #ArtificialInteligence

Check out this blog post on AI CardioTechx BCMHouston Texas Children's Sahar Samimi, MD blogs.bcm.edu/2025/03/07/art…

🚨 CardioTechX Journal Club Episode🚨 In this episode we're highlighting a novel #MachineLearning model that identifies #AF patients that benefit most from #LAAO vs. #DOAC. Full manuscript found here: jacc.org/doi/full/10.10… #CardioTwitter #MedEd #Cardiology

🚨 New CardioTechX Journal Club Episode 🚨 Can an AI-enabled ECG detect diastolic dysfunction as well as echo? 📉 A novel deep learning model identifies LV filling pressures & diastolic grades with impressive accuracy (AUC up to 0.94) — even in echo-indeterminate cases.

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After our recent 📖 featuring ADAPT-HEART, an AI-ECG model to detect structural 🫀 disease from 1-lead ECGs, thrilled to share another application of ⌚️/📱-based AI-ECG models to predict incident HF using 1-lead ECGs! Stay tuned for more from us CarDS Lab Yale Cardiology!

Meet infinite possibilities with Flow and Veo 3. 🎬 ✨Catch up on all the latest Google AI announcements and demos from #GoogleIO → ai.google

🧠💓 Deep learning meets congenital heart disease. This AI-ECG model predicted future LV dysfunction months before echo. You need to see this. #AIinMedicine #Cardiology #MedEd Josh Mayourian #CardioTwitter #CardioTech #ACHD #CHD #EchoFirst #HeartFailure2025 #HeartHealth

🚨 Introducing ECGFounder, a foundation model trained on over 10 million annotated ECGs, achieving expert-level performance across 150 diagnoses. Validated across diverse datasets, it generalizes well, even with single-lead inputs. NEJM AI Link: ai.nejm.org/doi/abs/10.105…

Open it. Zoom it. Save it. Share it. This is your go-to guide for standard adult TTE views.

I've always believed that using the "M" or "W" pattern recognition for diagnosing bundle branch blocks (BBB) should be discouraged. These patterns often don't apply to many cases of either left or right BBB. It's far more effective to teach why a particular BBB appears the way it

Pitfalls and promise in #AI/DL #EchoFirst: how to best evaluate the evaluation metrics to address bias? New #JACCIMG study evaluates 3 common challenges in EF estimation to mitigate these challenges for new AI/DL frameworks in #cvImaging. jacc.org/doi/10.1016/j.… #DeepLearning

📢 New #EHJ study! Our AI screening tool for echo — EchoGo® Amyloidosis — detects cardiac amyloidosis, a life-threatening condition, with high accuracy. Developed with Mayo Clinic The University of Chicago, tested with 18 global sites. See paper & release: ultromics.com/press-releases… #CardioTwitter

Excited to see this comparison of amyloid detection algorithms in JACC Journals #advances, lead by Faraz. AI algorithms on #echofirst outperform EHR and rules-based approaches. Similar AUC but different calibration. InVision Medical Technology Corporation more specific, Ultromics more sensitive.