Active Studies
The CarDS Lab conducts research through two primary approaches: retrospective data analysis and prospective clinical trials.
Retrospective studies utilize existing clinical data, including electronic health records and diagnostic results, to develop and validate artificial intelligence models for cardiovascular disease detection. These studies enable large-scale pattern recognition and hypothesis generation without direct patient involvement.
Prospective clinical trials assess the performance of these models in real-world settings. This approach uses gold-standard clinical trials to assess AI model accuracy, clinical utility, and impact on patient care, ensuring technologies are both data-driven and clinically validated.
Explore a featured list of active studies currently underway at the CarDS Lab below.
Retrospective Studies
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TRACE-AI is a multi-center observational study evaluating the ability of artificial intelligence (AI) to detect transthyretin amyloid cardiomyopathy (ATTR-CM) in adults undergoing routine cardiac testing, using ECG, point-of-care ultrasound, and echocardiogram data, with outcomes confirmed through medical records and diagnostic history.
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Clinical Trials
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DISCOVER-ATTR Pilot Study is a single-center observational registry aimed at piloting the development of a decentralized, patient-powered digital registry for transthyretin amyloid cardiomyopathy (ATTR-CM). This study will capture multimodal patient data from electronic health records (EHRs) and wearable devices to evaluate the feasibility of remote patient enrollment and data collection.
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DETECT-AS Diagnostic is a multi-site randomized clinical trial to assess the performance of artificial intelligence (AI) risk predictions to detect aortic stenosis using results from portable electrocardiogram (ECG) and cardiac ultrasound devices.
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DETECT-AS Prognostic is a multi-site prospective cohort study evaluating how well artificial intelligence (AI) can predict the progression of early-stage aortic valve disease using follow-up heart ultrasound results and clinical data.
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Precardia is an observational study to assess the use of smartwatches and wearable devices in monitoring cardiovascular health. The study will enroll up to 10,000 participants, collecting data from wearable devices and electronic medical records over five years to explore patterns and associations with cardiovascular health.
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TRACE-AI Yale Diagnostic is a single-site clinical study evaluating the accuracy of artificial intelligence (AI) in detecting transthyretin amyloid cardiomyopathy (ATTR-CM) in heart failure patients, using ECG and echocardiogram results, with confirmation through cardiac amyloid scans.
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