AI and Medical Insights

EchoNext FDA-cleared ECG screening for six structural heart diseases: What it means for echo capacity, referrals, EHRs, and medicolegal risk. Clinical Takeaway: Pathway Labs' EchoNext is FDA-cleared to identify six forms of structural heart disease (SHD) and to indicate a need for further echocardiogram. The scarce resource here is NOT the algorithm, but rather the ECG, which is an inexpensive resource. It is the downstream echo slot, the cardiology visit, and the clinician's time spent as to how to act with a flagged "normal" ECG.( Source:  Cardiovascular Business . ) What Was Actually Cleared (and a Framing Correction)? This article assumes six alerts of some sort are triggered on a “normal” ECG. The reported clearance is shallower, and therefore, the first thing to do is to identify the function of the tool. The six indications: The clearance includes both right- and left-sided heart failure, as well as valve disease, severe hypertrophy consistent with infiltrativ...

Discover how AI predicts sudden cardiac death using ECG, MRI, and EHR data, plus the latest research, accuracy, and clinical progress. Sudden cardiac death (SCD) is unexpected death due to an arrhythmia that occurs without an apparent cause of death in most people with no previous heart disease. Only a small proportion of people at risk can be identified by traditional screening, which currently mostly relies on low left-ventricular ejection fraction (LVEF). Artificial intelligence (AI) techniques have yielded some interesting results in the last few years in discovering potential clues to SCD in routine data. These researchers have trained deep learning models on vast amounts of data consisting of 12-lead electrocardiograms (ECGs), imaging (MRI/echo), electronic health records (EHR), and even multimodal data (which combines these sources of information) to make predictions about whether ostensibly healthy patients carry lethal arrhythmic risk. Key studies (2020-2026) showed that AI mo...

Foundation AI models are transforming cardiovascular medicine with smarter diagnosis, precision treatment, and better heart outcomes. Despite all the recent improvements in prevention and treatment, cardiovascular disease remains the leading cause of death in the world and a large proportion of the damage is done without the person ever knowing. A normal routine ECG can contain signs of heart failure, valve disease and dangerous muscle thickening for many years. The FDA has approved an AI system called EchoNext on June 23, 2026, which can identify six of these hidden conditions from a simple 12-lead electrocardiogram (ECG), the same test that doctors would conduct in their offices on a daily basis. This one approval is just a sign of the times that cardiology is on the verge of entering the foundation model era. It explains what foundation AI models are, how the science is already being applied in actual healthcare settings, and the future of the field without the hype or the jargon....

Find out how AI-powered ECG combines artificial intelligence with electrocardiography to improve heart disease detection and clinical decision-making. Introduction What if you went to a clinic for a routine check-up ECG and were told that you might have a serious condition developing in your heart before you even had any symptoms? No longer a daydreamer's dream. The field of electrocardiography is undergoing a transformation driven by the power of artificial intelligence (AI), as the technology uncovers the intricate details of heart signals that are beyond the consistent ability of the human eye. Cardiovascular diseases (CVD) are still one of the major causes of death globally. The power of early diagnosis is vital to better outcomes, and AI-driven electrocardiograms (ECGs) are becoming a useful tool for helping clinicians identify arrhythmias, the risk of heart failure, and patients needing further evaluation. While a clinician's experience is used to interpret an ECG in the ...