June 2, 2026 — AccurKardia, Inc. has been granted US Patent No. 12,620,488 for the company's proprietary machine-learning-based system for identifying cardiac amyloidosis from a standard, routinely performed 12-lead ECG.
Cardiac amyloidosis is a serious, often fatal heart disease in which abnormal proteins build up in heart tissue, causing the heart muscle to stiffen and eventually fail. Only recently recognized as a leading cause of heart failure in older adults, the condition remains widely underdiagnosed. Most patients are identified only after permanent damage to the heart has already occurred. The stakes of earlier detection are high and concrete: it impacts which treatments patients receive and how long they live. In heart failure clinics, studies estimate that roughly 13-15 percent of patients have undiagnosed cardiac amyloidosis.i Catching it sooner steers patients away from standard heart failure treatments that may be ineffective or even harmful for this condition, and toward therapies proven to improve survival.
"Cardiac amyloidosis hides in plain sight, and because the symptoms are quite similar to other causes of heart failure, we have historically relied on expensive, late-stage imaging to diagnose what is already advanced disease, often after conventional medical therapy has failed to improve symptoms," said Dr. Jason Lazar, executive vice dean, chair of the Department of Medical Education and Director of Non-invasive Cardiology at SUNY Downstate. “A reliable ECG-based screening signal, leveraging information the human eye simply cannot extract, has the potential to redefine when and how we intervene, particularly as therapeutic options continue to expand. Simply put, earlier diagnosis leads to much better outcomes.”
AccurKardia's Approach
AccurKardia’s patent establishes its intellectual property foundation across all major amyloidosis subtypes, including AL amyloidosis and wild-type and hereditary ATTR amyloidosis. It joins a growing pipeline of AccurKardia AI-ECG biomarkers that includes FDA Breakthrough Device-designated algorithms for aortic stenosis (AK-AVS™) and hyperkalemia (AK+ Guard), alongside the company's FDA-cleared automated ECG interpretation platform, AccurECG 2.0.
"Disease-modifying amyloidosis therapies are among the most important advances in cardiology in a generation, but their impact is gated by our ability to find the right patients in time," said Juan C. Jimenez, co-Founder and CEO of AccurKardia. "This patent establishes the foundation for closing that gap. We are turning a test that is already performed millions of times per year globally into a screening biomarker, deployable without new hardware or procedures, seamlessly integrating our capabilities into existing workflows."
A distinguishing feature of AccurKardia's approach is its use of explainable, feature-based machine learning, built on annotated ECG parameters, rather than a “black box” model. The design supports interpretability for clinicians, transparency for regulators, and adaptability for downstream deployment at scale.
i See, ASY, Ho, JS, Chan, MY, et. al. Prevalence and Risk Factors of Cardiac Amyloidosis in Heart Failure: A Systematic Review and Meta-Analysis. Heart Lung Circ. 2022 Nov;31(11):1450-1462. doi: 10.1016/j.hlc.2022.08.002. Epub 2022 Sep 20. PMID: 36137915.
October 21, 2025 
