News
Us2.ai, a leader in AI-automated echocardiography solutions and Advara HeartCare, the largest provider of cardiac healthcare services in Australia, are excited to announce a pilot aimed at enhancing heart disease detection, diagnosis and treatment. This pilot brings Us2.ai’s cutting-edge AI automated echocardiography solution to TickerCardiology, Advara HeartCare’s echocardiogram PACS software, to enhance the delivery of…
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New research led by the University of Dundee, demonstrated the feasibility of AI to automatically identify and classify patients with heart failure from archived echocardiographic images with Us2.ai software. Heart failure (HF) is a highly prevalent yet under-diagnosed condition with high mortality and morbidity. Echocardiography is a foundational investigation to diagnose HF and differentiate the types of HF i.e. HF with reduced (HFrEF), mildly reduced (HFmrEF)…
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Us2.ai automatically generates clinically relevant and reproducible quantitative echocardiographic left ventricular (LV) measurements, eliminating human intra-operator variability and reducing analysis time, as reported in Nature Communications. A study presented at ACC.24 aimed to assess the effectiveness of Us2.ai when utilizing ultrasound enhancing agents. The results indicated a strong agreement between human interpretations and AI, validating…
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New research using Us2.ai in comparison to gold standard invasive hemodynamic measurement showed that in patients with HFpEF, AI measurements of echo parameters are interchangeable with manual core-lab measures to diagnose increased filling pressures. “Evaluation of left ventricular filling pressures using non-invasive techniques is the holy grail of cardiac imaging in the setting of heart…
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Singapore – April 5, 2024 — Us2.ai, a leading MedTech firm backed by prominent investors including IHH Healthcare, Heal Partners, Peak XV Partners (formerly Sequoia India) and EDBI announces FDA clearance for Us2.v2, featuring 45 automated echo parameters, including strain analysis [1], marking a significant stride in medical innovation. Us2.v2 is an advanced image post-processing…
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Manual interpretation of echocardiographic data is time-consuming and operator-dependent. With the advent of artificial intelligence (AI), there is a growing interest in its potential to streamline echocardiographic interpretation and reduce variability. This study published in The Journal of Echocardiography aimed to compare the time taken for measurements by AI to that by human experts. “Our…
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Each year, RHD kills nearly 400,000 people globally. Experts at Children’s National Hospital deployed algorithms on the Us2.ai platform to detect early-stage RHD with the same accuracy as a cardiologist. “AI will tell you to move (the probe) left or right to get the ideal picture… Even more importantly, we’ve developed technology that can tell…
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The CUMIN study and implications for global healthcare, published in European Heart Journal Digital Health. “The study’s findings have broader implications, especially for healthcare systems facing resource constraints. The feasibility demonstrated in detecting cardiac dysfunction through AI-POCUS, even with novice operators, suggests a scalable and cost-effective solution. This could potentially reshape the landscape of HF…
Read MoreComments from Izabella Uchmanowicz, RN, PhD, FESC, FHFA The CUMIN pilot study published in European Heart Journal Digital Health represents a groundbreaking initiative in overcoming a significant healthcare challenge, particularly in low- and middle-income countries. The study’s focus on utilizing artificial intelligence-enhanced point-of-care ultrasound (AI-POCUS) in a home-based setting, led by novice nurses, provides a…
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CMS has issued a new HCPCS code for echocardiography image post processing for computer aided detection of heart failure with preserved ejection fraction, including interpretation and report and the timing could not be better for doctors and patients given our ability to completely automate the detection of all types of heart failure (HFpEF, HFrEF, HFmrEF)…
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