Tempus ECG-AF is a cardiovascular machine learning-based notification software intended to analyze recordings of 12-lead ECG devices from patients 65 years of age and older. The software employs machine learning techniques to analyze ECG recordings and detect signs associated with a patient experiencing atrial fibrillation and/or atrial flutter (collectively referred to as AF) within the next 12 months. The device is designed to extract otherwise unavailable information from ECGs conducted under the standard of care, to help health care providers better identify patients who may be at risk for undiagnosed AF in order to evaluate them for referral of further diagnostic follow up and address the unmet need of reducing the number of undiagnosed AF patients.
A software program designed to add image processing and/or data analysis capabilities to a computer/workstation for the interpretation and/or screening of cardiopulmonary physiological parameters [e.g., electrocardiogram (ECG), blood pressure, vital capacity (VC)]; data may be uploaded, or collected in real-time by connection (e.g., wired, Bluetooth) to other devices for spot-checks and/or continuous monitoring. It is intended for use exclusively by healthcare professionals and may provide risk assessment for cardiopulmonary events [e.g., acute myocardial infarction (AMI)] or screen for specific conditions (e.g., low ejection fraction). It might include machine learning (ML) technology.
tempus.com