Heart Matters



  Guest: Patricia A. Pellikka, M.D. 


  
    Artificial intelligence (AI) has several applications in cardiology, such as echocardiography. Can machine learning and AI algorithms in echocardiology help clinicians better detect heart failure with preserved ejection fraction (HFpEF)? Dr. Patricia A. Pellikka, Director of the Ultrasound Research Center at the Mayo Clinic, shares data from ACC.23 and explores the potential of AI in detecting HFpEF.

Exploring the Use of AI to Detect HFpEF


Exploring the Use of AI to Detect HFpEF
 | CastVibes

Treating Tricuspid Valve Regurgitation With Novel Replacement Device


Guest: Patricia A. Pellikka, M.D. 


  
    Artificial intelligence (AI) has several applications in cardiology, such as echocardiography. Can machine learning 



  Host: Javed Butler, MD <br>

  Guest: Chiadi Ndumele, M.D., Ph.D., M.H.S. <br>


  
    <p>For the first time, the American Heart Association (AHA) has identified cardiovascular-kidney-metabolic (CKM) syndrome, which reflects a strong overlap between heart disease, kidney disease, and obesity. The major clinical consequence of CKM syndrome is multi-organ dysfunction with a particularly high incidence and burden of cardiovascular disease (CVD), and the result of this is premature morbidity and mortality. So as a result, recognizing CKM syndrome is the first step in earlier diagnosis and treatment. Dive into this episode with Dr. Javed Butler who’s joined by Dr. Chiadi Ndumele, Associate Professor of Medicine and the Director of Obesity and Cardiometabolic Research at Johns Hopkins University.</p>