CardioTechx
@CardioTechx
CardioTechx by @SaharSamimii & @DonnchadhOSull | Keep up-to-date with rapidly evolving Cardiology, Technology & Artificial Intelligence Research | Our own views
How should we compare AI mistakes vs human mistakes in healthcare? Doctors make mistakes all the time, but it’s not like we remove the medical license of a doc if they make a few mistakes. The bar for AI is way higher - it has to be nearly perfect and tested in every possible…
EchoNext, a DL ECG model trained on 1.2M ECG–echo pairs, prospectively identified previously undiagnosed SHD (PPV>50%) and exceeded cardiologist performance across 11 hospitals. Public weights + 100k-labeled ECG set released. doi.org/10.1038/s41586… #AIinMedicine #CardioTwitter…
🚨Releasing 200k cardiac MRI images! 🚨 Open source cMRI datasets contain only a few hundred images, so we used GANcMRI to create 1000x bigger fully synthetic dataset. We hope that GANcMRI dataset will boost the development of AI models for cardiology.
Excited to see this comparison of amyloid detection algorithms in @JACCJournals #advances, lead by @FarazAhmadMD. AI algorithms on #echofirst outperform EHR and rules-based approaches. Similar AUC but different calibration. @InVision_AI more specific, @ultromics more sensitive.…
📢 New #EHJ study! Our AI screening tool for echo — EchoGo® Amyloidosis — detects cardiac amyloidosis, a life-threatening condition, with high accuracy. Developed with @MayoClinic @UChicago, tested with 18 global sites. See paper & release: ultromics.com/press-releases… #CardioTwitter
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
Open it. Zoom it. Save it. Share it. This is your go-to guide for standard adult TTE views.
🚨 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……
🧠💓 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 @jmayour #CardioTwitter #CardioTech #ACHD #CHD #EchoFirst #HeartFailure2025 #HeartHealth…
Meet infinite possibilities with Flow and Veo 3. 🎬 ✨Catch up on all the latest Google AI announcements and demos from #GoogleIO → ai.google
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 @YaleCardiology!
Excited to share our 🆕 pub demonstrating the power of #AI in detecting #HF risk in single-lead ECGs across diverse cohorts 🇺🇸🇬🇧🇧🇷 Led by 🌟 lab members @LovedeepDhingra @AryaAminorroaya Read the 📄 in @jamacardio: jamanetwork.com/journals/jamac… @rohan_khera @YaleMed @YaleCardiology
Humbled that @NajvaApp has hit 1000+ users! I've dictated 100K+ words with it - it's become an inseparable part of my workflow. Voice-to-text + LLM is the ultimate productivity tool. Try it yourself (always free) and feel the magic! 🎙️✨ najva.brdkhsrv.com
🚀 Najva 2.0 is HERE! We've just hit 1,000 users and we're celebrating with our biggest update yet. Enjoy advanced reasoning models like o3, o4-mini, and Gemini 2.5 Flash, plus GPT-4.5 and Claude 3.7 Sonnet support! Download now (free): bardiakhosravi.gumroad.com/l/najva #STT #macOS /1
🚨 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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