Tempus ECG-AI Solutions

Overview

Tempus accelerates cardiac care with AI-powered solutions designed to support clinicians in identifying patients who may be at risk for a variety of cardiovascular conditions.

Features

Tempus ECG-AI devices are deployed together with advanced cardiology algorithms to detect signs associated with certain cardiovascular conditions and notify care teams for patient follow-up.

Step 1: Patient filtering

Tempus employs EHR integrations and patient clinical data to filter patients that may be eligible for Tempus ECG-AI device use based on IFU criteria.

Step 2: Patient diagnosis

Tempus is pursuing development of Tempus ECG-AI based cardiology algorithms that can analyze physiological inputs using machine learning models, and detect signs associated with certain cardiovascular conditions for further referral or diagnostic follow-up.

Step 3: Patient follow-up

Tempus uses AI to identify and contextualize patients in their journey, surface precision pathways at the point of care and track patients for further referral or diagnostic follow-up consistent with clinical care guidelines.

FDA Cleared, Tempus ECG-AI Devices

All Tempus ECG-AI solutions are designed to work with existing ECG platforms and EHRs to enable advanced AI deployment and insights within clinical workflows.

Tempus ECG-AF

Intended Use: The Tempus ECG-AF algorithm is intended for use to analyze recordings of 12-lead electrocardiogram (ECG) devices and detect signs associated with a patient experiencing AF within the next 12 months. It is for use on resting 12-lead ECG recordings collected at a healthcare facility from patients 65 years of age or older who do not have a known history of AF or other specified conditions. The device provides clinicians with results that should be interpreted in conjunction with other diagnostic information, including the patient’s original ECG recordings and other tests, as well as the patient’s symptoms and clinical history. Tempus ECG-AF does not describe a person’s overall risk of experiencing AF and should not serve as the sole basis for diagnosis of AF. Results should not be used as the basis for treatment of AF and are not intended to rule out AF follow-up.¹

Read the press release ↗︎

Algorithm design: The Tempus ECG-AF model was trained on de-identified data from >1,500,000 ECGs and >500,000 patients.¹
Results: For patients receiving a positive result from the Tempus ECG-AF test, AF would be observed in approximately 1-in-5 patients within the next 12 months.¹

Tempus ECG-Low EF

Intended use: Tempus ECG-Low EF only analyzes ECG data and provides a binary output for interpretation. Tempus ECG-Low EF is not intended to be a stand-alone diagnostic tool for cardiac conditions, should not be used for patient monitoring, and should not be used on ECGs with paced rhythms. Results should be interpreted in conjunction with other diagnostic information, including the patient’s original ECG recordings and other tests, as well as the patient’s symptoms and clinical history. A positive result may suggest the need for further clinical evaluation in order to establish a diagnosis of low LVEF. Patients receiving a negative result should continue to be evaluated in accordance with current medical practice standards using all available clinical information.²

Read the press release ↗︎

Algorithm design: The Tempus ECG-Low EF model was trained on de-identified data from >930,000 ECGs and >170,000 patients.²
Results: For patients receiving a positive result from the Tempus ECG-Low EF test, LVEF (≤40%) would be observed in approximately 2-in-5 patients when tested by echocardiogram.²

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CPT Coding for ECG-AI Devices

Effective January 1, 2025, CPT3 +0764T and 0765T are listed under the Hospital Outpatient Prospective Payment and Ambulatory Surgical Center Payment Systems (OPPS) as Category III codes to describe assistive algorithmic electrocardiogram assessments for cardiac dysfunction.

Predictive ECG algorithms for undiagnosed disease

Tempus’ portfolio aims to support clinicians in identifying patients who may be at risk for a variety of cardiovascular conditions.

Pipeline current as of 01/2026

Our science

Advancing cardiac care through algorithm development, validation, and scaled clinical adoption.

ALERT study: Addressing undertreatment and health equity in aortic stenosis and mitral regurgitation using an integrated EHR platform

This multi-center, prospective, cluster-randomized controlled trial will evaluate automated notifications as an intervention to support identification and evaluation of patients possibly indicated for a transcatheter or surgical procedure to treat aortic stenosis or mitral regurgitation.

MOMENTOUS Study: Assessing the clinical impact of an ECG algorithm to increase the diagnosis of pulmonary hypertension

Tempus is sponsoring a multi-site study of an investigational AI algorithm that analyzes the results of a 12-lead electrocardiogram (ECG) to find patients at increased risk of having undetected pulmonary hypertension (PH). Clinicians will evaluate the AI’s ability to detect patients at risk of undiagnosed PH, and will track clinical outcomes of patients who are identified for further evaluation.

NOTABLE Study

The NOTABLE (NOrthwestern Tempus AI-enBLed Electrocardiography) study will examine rates of new disease diagnosis, therapeutic interventions, and cardiovascular outcomes in patients managed by clinicians at Northwestern Medicine who use ECG predictive models compared to patients managed by clinicians at Northwestern Medicine who do not use the ECG predictive models.

ECG AID Study

This study, which recently completed enrollment, will investigate the prospective performance of our algorithms for atrial fibrillation and structural heart disease.

Tempus Receives U.S. FDA 510(k) Clearance for Tempus ECG-Low EF Software

Tempus AI, Inc. (NASDAQ: TEM), a technology company leading the adoption of AI to advance precision medicine and patient care, today announced it has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its Tempus ECG-Low EF (ejection fraction) algorithm, which uses AI to detect signs associated with having a low left ventricular ejection fraction (LVEF ≤40%) in patients 40 years of age or older at risk of heart failure.

Tempus Receives U.S. FDA 510(k) Clearance for Tempus ECG-AF, an AI-based Algorithm that Identifies Patients at Increased Risk of AFib

Tempus AI, Inc. (NASDAQ: TEM), a leader in artificial intelligence and precision medicine, today announced it has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its Tempus ECG-AF device that uses AI to help identify patients who may be at increased risk of atrial fibrillation/flutter (AF).

New CMS Decision Provides Medicare Coverage for the Clinical Use of the Tempus ECG-AF Device

Tempus AI, Inc. (NASDAQ: TEM), a technology company leading the adoption of AI to advance precision medicine and patient care, today announced the impact of a new decision by the Centers for Medicare and Medicaid Services (CMS) that will allow reimbursement for assessments of cardiac dysfunction using the Tempus ECG-AF algorithm

Tempus and Northwestern Medicine Announce Collaboration to Bring Practical Application of AI to Healthcare

Tempus, a leader in artificial intelligence and precision medicine, and Northwestern Medicine, Chicago’s premier integrated academic health system, today announced a collaboration that aims to explore the application of artificial intelligence in clinical care and research.

Enhancing Diagnostic Accuracy and Treatment Appropriateness in Cardiac Transthyretin Amyloidosis Through Natural Language Processing: A Retrospective Analysis

Development of Machine Learning Models Incorporating Clinical, Demographic, and Echocardiography Variables for Predicting Left Ventricular Systolic Dysfunction in Patients With Isolated Left Ventricular Dilation

Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation–Related Stroke

Implementation of EHR-Integrated Notifications on Patients at Risk for Sudden Cardiac Arrest. Kelley, T, Rink, C, Sotelo, M. et al.

Development and validation of a moderate aortic stenosis disease progression model

Learn more about joining a study or partnering with Tempus on research →

Resources

References

INDICATIONS FOR USE: Tempus ECG-AF is intended for use to analyze recordings of 12-lead ECG devices and detect signs associated with a patient experiencing atrial fibrillation and/or atrial flutter (collectively referred to as AF) within the next 12 months. It is for use on resting 12-lead ECG recordings collected at a healthcare facility from patients: 65 years of age or older, without pre-existing or concurrent documentation of atrial fibrillation and/or atrial flutter, who do not have a pacemaker or implantable cardioverter defibrillator, and who did not have cardiac surgery within the preceding 30 days. Performance of repeated testing of the same patient over time has not been evaluated and results SHOULD NOT be used for patient monitoring. Tempus ECG-AF only analyzes ECG data. Results should be interpreted in conjunction with other diagnostic information, including the patient’s original ECG recordings and other tests, as well as the patient’s symptoms and clinical history. Tempus ECG-AF is not for use in patients with a history of AF, unless the AF occurred after a cardiac surgery procedure and resolved within 30 days of the procedure. It is not for use to assess risk of occurrence of AF related to cardiac surgery. Results do not describe a person’s overall risk of experiencing AF or serve as the sole basis for diagnosis of AF, and should not be used as the basis for treatment of AF. Results are not intended to rule-out AF or the need for follow-up. Link to IFU: https://www.tempus.com/ifu-ecg-af/
INDICATIONS FOR USE: Tempus ECG-Low EF is software intended to analyze resting, non-ambulatory 12-lead ECG recordings and detect signs associated with having a low left ventricular ejection fraction (LVEF less than or equal to 40%). It is for use on clinical diagnostic ECG recordings collected at a healthcare facility from patients 40 years of age or older at risk of heart failure. This population includes but is not limited to patients with atrial fibrillation, aortic stenosis, cardiomyopathy, myocardial infarction, diabetes, hypertension, mitral regurgitation, and ischemic heart disease. Tempus ECG-Low EF only analyzes ECG data and provides a binary output for interpretation. Tempus ECG-Low EF is not intended to be a stand-alone diagnostic tool for cardiac conditions, should not be used for patient monitoring, and should not be used on ECGs with paced rhythms. Results should be interpreted in conjunction with other diagnostic information, including the patient’s original ECG recordings and other tests, as well as the patient’s symptoms and clinical history. A positive result may suggest the need for further clinical evaluation in order to establish a diagnosis of low LVEF. Patients receiving a negative result should continue to be evaluated in accordance with current medical practice standards using all available clinical information. Link to IFU: https://www.tempus.com/ifu-ecg-low-ef/
CPT® Copyright 2024 American Medical Association. All rights reserved. CPT is a registered trademark of the American Medical Association. Applicable FARS/DFARS Restrictions Apply to Government Use. Fee schedules, relative value units, conversion factors, and/or related components are not assigned by the AMA, are not part of CPT®, and the AMA is not recommending their use. The AMA does not directly or indirectly practice medicine or dispense medical services. The AMA assumes no liability for data contained or not contained herein.

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