What You Should Know
– AliveCor, the global leader in AI-powered cardiology, has received U.S. FDA clearance for the next generation of its KAI 12L AI. This update expands the diagnostic breadth of the Kardia…
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Marie Hattar, SVP at Keysight Technologies
Wearable devices are transforming healthcare through continuous monitoring, early detection, and personalized management of chronic diseases. These innovations are reinventing how health concerns are tracked and treated, with the goal of improving…
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What You Should Know
– AccurKardia has announced its second FDA 510(k) clearance for the AccurECG™ Analysis System (v2.0). This enterprise-grade, cloud-based platform is designed to ingest data from any ECG hardware—including patches and Holters—and…
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What You Should Know:
– Wearlinq has secured $14M in Series A funding (plus $5M in venture debt) to scale its eWave device, the first continuous 6-lead wireless ECG that offers hospital-grade diagnostics in a…
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Artificial intelligence-enhanced electrocardiogram (AI-ECG) models have shown outstanding performance in diagnostic and prognostic tasks, yet their black-box nature hampers clinical adoption. Meanwhile, a growing demand for explainable AI in medicine underscores the need for…
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What You Should Know:
– The U.S. Food and Drug Administration (FDA) has recently issued several key clearances, marking significant advancements across diagnostics, surgery, and remote patient monitoring.
– These FDA clearances reflect a deepening integration…
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Current AI approaches for cardiac diagnosis require condition-specific supervised learning with extensive labeled datasets, leading to fundamental scalability barriers. We developed an ECG-CLIP model, applying contrastive multimodal learning to enable zero-shot cardiac diagnosis from…
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Tricuspid regurgitation (TR) remains underdiagnosed due to the lack of effective screening tools. We developed a self-distilled and pre-trained transformer model for detecting TR (SPEED-TR) from electrocardiography. The model was trained using 466,149 electrocardiogram-echocardiogram…
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Cardiovascular diseases remain the leading cause of death in developed countries. This study introduces deep learning ensembles for arrhythmia detection and atrial fibrillation (AF) recurrence prediction from electrocardiogram scans, supported by explainable artificial intelligence…
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PreOpNet is a novel deep-learning algorithm using 12-lead digital electrocardiogram (ECG) for preoperative risk assessment of all-cause death and major adverse cardiac events (MACE) within 30 days. Its performance in European high-risk patients undergoing…
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