NOrthwestern Tempus AI-enaBLed Electrocardiography (NOTABLE) Trial
Sponsored by Northwestern University
About this study
The goal of this clinical trial is to determine if a machine learning/artificial intelligence (AI)-based electrocardiogram (ECG) algorithm (rECHOmmend and ECG-AF) can identify undiagnosed cardiovascular disease in patients. It will also examine the safety and effectiveness of using this AI-based tool in a clinical setting. The main questions it aims to answer are: 1. Can the AI-based ECG algorithm improve the detection of atrial fibrillation and structural heart disease? 2. How does the use of this algorithm affect clinical decision-making and patient outcomes? Researchers will compare the outcomes of healthcare providers who receive the AI-based ECG results to those who do not. Participants (healthcare providers) will: Be randomized into two groups: one that receives AI-based ECG results and one that does not. In the intervention group, receive an assessment of their patient's risk of atrial fibrillation or structural heart disease with each ordered ECG. Decide whether to perform further clinical evaluation based on the AI-generated risk assessment as part of routine clinical care.
Enrolling at this location
Completing a questionnaire on Clinably does not enroll you in a clinical trial or confirm your eligibility. Only the research team can determine whether you qualify to participate. These results are based on the information you provide and are intended to help you start a conversation with the research team.
Trial data sourced from ClinicalTrials.gov.