Us2.ai’s Post

🚨 A team in the Netherlands investigated the AliveCor #kardiamobile #AI algorithms in ⚡ 85,000 ECGs ⚡ of 2,300 patients in the #Hartwacht program of our partner Cardiologie Centra Nederland and came up with really interesting results! 👉 Determination "Sinus Rhyhtm": PPV of 99.6% 👉 Determination "Possible AFib": Sensitivity of 98.9% or in other words: 💥 if the algorithm says "Sinus Rhythm" it is highly likely true 💥 The algorithm is very sensitive to detect Afib The authors conclude: "Standalone algorithm interpretation of Sinus Rhythm ECGs by the KardiaMobile algorithm, without additional manual checking, is feasible." #mhealth #digitalhealth #cardiology Bridget Slaats Sebastiaan Blok G. Aernout Somsen, MD PhD FACC FESC Igor Tulevski Renoud Knops Bert-Jan van den Born Michiel Winter David Albert Ben Green, MD Link to the full publication: https://lnkd.in/d_j_F2bi

What is the future of AI in cardiovascular care? In this episode of #AIMeetsLifeSci, Paul Friedman, MD, Chair of the Department of Cardiovascular Medicine at Mayo Clinic explains how generative and predictive AI work in order to help with #CardiovascularCare, he also speaks on the different forms of AI and how they can be used and their validity. Thank you to our contributors, some of whom include Catalyze Healthcare and SmartTRAK / BioMedGPS, LLC, for providing vital support. Watch this video clip below, and for the full episode, VISIT: https://lnkd.in/eU3MpE8D Kayleen Brown Tom Salemi Brian K. Buntz #cardiac #cardiology #ECG #AI

🎉 Exciting news from our team! - Evidence-based AI We’re thrilled to announce the recent publication of our proof-of-concept study in the Cureus Journal of Medical Science. Read it here: https://lnkd.in/d2JhAD3t We conducted the study in collaboration with the Northumbria Healthcare NHS Foundation Trust, supported by Northumbria University, St. George's University International School of Medicine, and University of Sunderland. Our study showcased the performance of the AIATELLA tool in the assessment of Cardiac MR imaging of the aortic root and valve. The tool was compared against three consultant cardiologists, demonstrating that it is as accurate as the cardiologists and can therefore be relied upon. What’s more, our AI tool produced results over 100x faster than the human experts in the study! This is a promising step forward for our AI, showing its potential to increase the efficiency of care delivery in Cardiovascular medicine. Our next steps are to validate our tool in a large, global cohort to demonstrate its generalisability. We’re fortunate to have research partners in the North East from the NHS, and internationally in Europe, the US, and India, who will be instrumental in this next phase. Stay tuned for more updates as we continue to push the boundaries of AI in healthcare! #aiinhealthcare #radiology #evidencebased #publication

What is the future of AI in cardiovascular care? In this episode of #AIMeetsLifeSci, Paul Friedman, MD, Chair of the Department of Cardiovascular Medicine at Mayo Clinic explains how generative and predictive AI work in order to help with #CardiovascularCare, he also speaks on the different forms of AI and how they can be used and their validity. Thank you to our contributors, some of whom include Catalyze Healthcare and SmartTRAK / BioMedGPS, LLC, for providing vital support. Watch this video clip below, and for the full episode, VISIT: https://lnkd.in/eU3MpE8D Kayleen Brown Tom Salemi Brian K. Buntz #cardiac #cardiology #ECG #AI

What is the future of AI in cardiovascular care? In this episode of #AIMeetsLifeSci, Paul Friedman, MD, Chair of the Department of Cardiovascular Medicine at Mayo Clinic explains how generative and predictive AI work in order to help with #CardiovascularCare, he also speaks on the different forms of AI and how they can be used and their validity. Thank you to our contributors, some of whom include Catalyze Healthcare and SmartTRAK / BioMedGPS, LLC, for providing vital support. Watch this video clip below, and for the full episode, VISIT: https://lnkd.in/eU3MpE8D Kayleen Brown Tom Salemi Brian K. Buntz #cardiac #cardiology #ECG #AI

Interesting study which shows that infrared, when augmented by AI, can be effective can be effective in screening for coronary artery disease. While an initial report, the results are impressive. What’s cool here is that the AI is enabling low cost and universally available technologies to take the place of high cost and high risk assessment tools. We’ll still need to verify disease severity with CT and treat with cath procedures, but now we’ve got something that can be used much more broadly. Put succinctly, this could be a real game changer: improve availability, enable early detection, and drive down costs.

This is an impressive application of AI that can elevate cardiovascular disease screening to a whole new level !👇 Traditionally, coronary artery diseases (CAD) are initially assessed by evaluating risk factors and symptoms (pre-test probability: PTP), which often have limited performance. This team used infrared thermography (IRT)—a technology that assesses surface temperature without skin contact—to predict CAD. The results are impressive: “The IRT image model demonstrated outstanding performance (AUC 0.804) compared to traditional PTP models (AUC 0.713).” This type of contactless technology, which is more accessible and far less invasive than CT and coronary angiography, combined with AI analysis, has the potential to significantly enhance the detection of cardiovascular diseases at scale. More broadly, AI's ability to extract clinically relevant information from common images that are not visible to human experts, as demonstrated here, opens up vast opportunities to improve the detection and analysis of human physiology and diseases. This is particularly true for radiology, which generates an immense amount of images every day, likely containing crucial information waiting to be unveiled by AI. Keep in mind that this study has several limitations, particularly the bias stemming from the inclusion of only high-risk CAD patients. Congrats to the team on this great study, and wishing everyone a fantastic start to the week ! #AI #thermography #facial #cardiology #CAD #screening Tsinghua University Link to the article in the comments 👇

new ECG realizes the quantification of ECG for the first time. (a) As the waveform images are {Qualitative diagnostics}, the identification of patterns may lead to controversy between individuals. (b) The data are {Quantitative diagnostics}, and the data have international standards and will not cause disputes. Contains three main aspects of data, (1) Non-invasive ECG data. (2) Invasive electrophysiologic data. (3) The data in the textbook is calculated based on the SAN, because the frequency of the SAN is the heart rate 60~100/bpm. The ECG data is only accurate in the R~R interval because the R wave is at an acute angle. In the new ECG, each wave has an acute angle, and all measurements are in milliseconds (ms). Why should the ECG be digitized? (a) Many disease images do not change, but the data does. (b) Many images have changed and must be identified on the basis of the data. (c) For many non-occurring diseases, the image does not change, but the data changes first {For example: CAD, heart failure, AVNRT/AVRT, etc.} If you find them useful, worth reading, please comment, like and share. PhysioSign USA #ecg #noninvasive #ep #cardiology #electrophysiology #ai #electrocardiogram

Great study using AI models to predict patient diagnosis and assess cardiac function, offering a non-invasive and efficient approach to cardiac care -> The study provides a non-invasive method to predict diagnosis of patients undergoing cardiac MRI and to obtain left ventricular end-diastolic pressure. -> The study identified 66936 patients with over 183772 individual left ventricular pressure measurements. -> The AI models classified the different types of cardiomyopathy with good accuracy. -> The AI models could be integrated into clinical practice and provide added value to the information content of cardiac MRI, allowing for disease classification and prediction of diastolic function. Read more on: https://lnkd.in/esFet85h The Lancet #digitalhealth #AI #cardiology

𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐢𝐧 𝐂𝐚𝐫𝐝𝐢𝐨𝐥𝐨𝐠𝐲 ❤️🩺 - Revolutionizing Diagnostics: AI-driven tools enhance accuracy in heart disease detection, improving patient outcomes faster than ever! 🕒💡 - Personalized Treatment Plans: With AI, cardiologists can tailor treatment strategies to individual patient needs, optimizing therapy efficacy. 🎯🧬 - Predictive Analytics: Harnessing AI to predict cardiac events before they occur, giving patients a proactive approach to heart health. 🔍🔮 - Research and Innovation: AI accelerates cardiology research by generating insights from complex datasets, unveiling new potentials in heart care. 📊🚀 Explore how AI is transforming cardiology with innovative insights! For rigorous literature reviews, visit https://www.sciqst.com. Dive deep into the future of heart care today! 💼👇 #ArtificialIntelligence #Cardiology #HealthcareInnovation #MedicalResearch #SciQst