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The purpose of this study is to evaluate the impact of bromocriptine on myocardial recovery and clinical outcomes in women newly diagnosed with peripartum cardiomyopathy within 5 months postpartum. Given that bromocriptine prevents breastfeeding, women with peripartum cardiomyopathy will be excluded from the trial due to a desire to continue breastfeeding but meeting all other entry criteria will be followed in an observational cohort.
The aim of this study is to compare artificial intelligence (AI) based disease predictions across different electrocardiogram (ECG) devices. The ECG is a test that records your heart’s rhythm. The goal is to evaluate the impact of ECG device type on AI-based heart disease predictions.
The overarching goal is to provide a means to evaluate cardiac allograft rejection non-invasively and remotely. This can be used to identify and prioritize patients that need to visit Mayo Clinic frequently following a heart transplant based on the likelihood of cardiac allograft rejection.
The overall goal of this study is to investigate the use of artificial intelligence (AI) techniques as a screening tool for cardiomyopathies in pregnancy and the post-partum period.
The purpose of this studyis to determine the effectiveness of an AI-enabled ECG to detect cardiomyopathy and its impact on clinical outcomes in a predominantly Black obstetric population in Nigeria
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