Mayo Clinic Cardiac Monitoring is an end-to-end solution that merges leading-edge remote monitoring technology with years of Mayo Clinic cardiac monitoring experience. Designed to simplify and streamline the remote monitoring process, our program seamlessly connects patients with innovative diagnostics, delivering an enhanced experience for patients and their healthcare providers. Fast, reliable, and accessible, Mayo Clinic Cardiac Monitoring fosters a healthier and more informed future for patients and their physicians.
“The device transmits data digitally in near real time, which gives us the answers we need when we need them.”
Peter Noseworthy, M.D.
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In this episode of the "Mayo Clinic Cardiovascular CME" podcast, Guru Kowlgi, M.B.B.S., and host Anthony Kashou, M.D., dive deep into the topic of deep-learning models for the prognostication and localization of premature ventricular contractions (PVCs) using a 12-lead ECG. This episode differentiates benign rom malignant PVCs and informs which patients are at risk for PVC-cardiomyopathy.
In this “ECG Segment: Making Waves” episode of the “Mayo Clinic Cardiovascular CME” podcast, host Anthony Kashou, M.D., interviews Michele Pelter, R.N., Ph.D., about ventricular tachycardia database development and detection.
In this “ECG Segment: Making Waves” episode of the “Mayo Clinic Cardiovascular CME” podcast, we explore emerging ECG methods for ischemia detection, delving into the limitations of the 12-lead ECG and discussing the latest advancements in ECG technology.
In this “ECG Segment: Making Waves” episode of the “Mayo Clinic Cardiovascular CME” podcast, we delve into ECG literacy and explore various approaches to teaching and learning this essential skill.
In this “ECG Segment: Making Waves” episode of the “Mayo Clinic Cardiovascular CME” podcast, host Anthony Kashou, M.D., discusses premature ventricular complexes (PVCs) with William G. Stevenson, M.D., a professor of medicine at Vanderbilt University Medical School.
In this “ECG Segment: Making Waves” episode of the “Mayo Clinic Cardiovascular CME” podcast, host Anthony Kashou, M.D., discusses the topic of Lyme carditis with expert Dr. Adrian Baranchuk. Lyme disease is a common tick-borne infection that can affect the heart, causing impaired electrical conduction and potentially serious complications if left untreated.
Ryan O’Hara, a Ph.D. candidate in biomedical engineering at Johns Hopkins University, joins Anthony Kashou, M.D., to discuss hypertrophic cardiomyopathy and how personalized computational heart models can be used to improve the risk stratification of these patients.
Peter Macfarlane, Ph.D., D.Sc., a University of Glasgow emeritus professor and honorary senior research fellow, joins host Anthony Kashou, M.D., to discuss the current and future role of computerized ECG interpretation.
Biomedical engineer and deep learning expert Alan Kennedy, Ph.D., joins hosts Anthony Kashou, M.D., for an in-depth discussion about device agnostic ECG interpretation and how it will affect the future of cardiology.
Bob Farrell, Ph.D., principle engineer in diagnostic cardiology at GE Healthcare in Milwaukee, Wisconsin, and current member of the board of directors of the International Society of Computerized Electrocardiology, joins host Anthony Kashou, M.D., to discuss how computerized electrocardiography can help physicians detect and treat left ventricular hypertrophy.
Juan Crestanello, M.D., chair of the Department of Cardiovascular Surgery at Mayo Clinic in Rochester, Minnesota, joins Kyle Klarich, M.D., to discuss aortic root enlargement, why it’s done, and which patients are the best candidates for the procedure.
Cardiac intensivist Adam May, M.D., joins Anthony Kashou, M.D., to discuss the different types of manual wide complex tachycardia differentiation methods available to clinicians today.
In a recent Mayo Clinic study, participants wore a continuous ambulatory heart rhythm monitor that transmitted their heart data to the Mayo Clinic team in real time. Researchers used a targeted strategy to apply artificial intelligence to the participants’ electrocardiogram data. As a result, they identified a subgroup of high-risk patients who could benefit from more intensive monitoring to detect atrial fibrillation. Doctors hope this approach can help in resource-limited environments, with the goal of connecting more patients to treatment to prevent strokes.
