FDA Radiology AI Devices

DeepRhythmAI is a cloud-based AI software that automatically analyzes two-lead ECG data to detect cardiac arrhythmias. It supports healthcare professionals by providing analysis results that need to be reviewed and confirmed. It is designed for integration into other medical devices or software platforms and assists clinicians in identifying rhythm issues in adult patients.

The ZEUS System (Zio Watch) is a prescription-based wearable device and software system that uses AI to analyze cardiac signals from an ECG and PPG sensor to detect and report atrial fibrillation. It provides clinicians with detailed reports to aid in diagnosing and managing atrial fibrillation in adult patients.

The Study Watch with Irregular Pulse Monitor by Verily Life Sciences is a wearable device designed for adults diagnosed with or at risk for atrial fibrillation (AF). It continuously monitors heart rhythms using photoplethysmography (PPG) and single-channel ECG measurements. The device notifies users of irregular pulses, prompting ECG collection, and securely transmits data for healthcare provider review. This aids early detection and monitoring of AF, enabling timely clinical intervention.

The Eko Murmur Analysis Software (EMAS) is a cloud-based AI-driven tool that analyzes heart sound and ECG data to detect and classify heart murmurs, distinguishing between innocent and structural murmurs. It supports clinicians by offering decision support in evaluating heart sounds, enhancing the diagnostic process for pediatric and adult patients without replacing clinical judgment.

The Atrial Fibrillation History Feature is a software application designed to analyze pulse rate data from Apple Watch sensors to detect episodes of irregular heart rhythm indicative of atrial fibrillation (AFib). It provides users with estimates of the amount of time spent in AFib over past periods and visualizes this alongside lifestyle data to help users understand the impact of their behavior on their condition. It assists patients in monitoring AFib burden over time but is not meant to replace traditional diagnosis or treatment methods.

DEEPVESSEL FFR is a clinical software tool that uses deep learning to analyze previously acquired coronary CT angiography (CTA) images. It generates three-dimensional models of coronary artery trees and estimates fractional flow reserve (FFR) values to help clinicians assess the functional severity of coronary artery disease. It supports doctors by providing additional insight beyond anatomical imaging, using AI-based physiological simulation to improve diagnosis and treatment planning for heart vessel conditions.

The AHI System is a software tool that helps healthcare professionals monitor adult patients' cardiovascular status by analyzing ECG signals to detect signs of current hemodynamic instability and predict future episodes. It provides continuous updates and color-coded alerts for clinicians to increase vigilance and improve patient care.

IM007 by Implicity, Inc. is an AI-powered software that analyzes ECG data from Insertable Cardiac Monitors to help healthcare professionals detect various cardiac arrhythmias, such as atrial fibrillation and ventricular tachycardia. It works by processing ECG signals remotely uploaded from compatible devices and provides analysis results to clinicians to support diagnosis and patient monitoring.

The Irregular Rhythm Notification Feature 2.0 (IRNF 2.0) is a software application used on Apple Watch and iPhone that analyzes pulse rate data using machine learning to detect irregular heart rhythms, such as atrial fibrillation (AFib). It notifies users of possible AFib episodes to help prompt medical consultation, supporting non-invasive heart rhythm monitoring through wearable technology.

FEops HEARTguide is a software tool that helps clinicians simulate and plan the implantation of left atrial appendage occlusion devices in individual patients. By using CT scans to create patient-specific heart models and incorporating device mechanics, it predicts how the device will deform and interact with the tissue, aiding pre-procedural decision-making to improve procedural outcomes and device placement.