AATS: Machine Learning-Derived Risk Model to Predict Post-Cardiotomy Cardiogenic Shock in High-Risk Cardiac Surgery Patients

Cardiac Consult: A Cleveland Clinic Podcast for Healthcare Professionals

A tartalmat a Cleveland Clinic Heart & Vascular Institute, Cleveland Clinic Heart, and Vascular Institute biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Cleveland Clinic Heart & Vascular Institute, Cleveland Clinic Heart, and Vascular Institute vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

17d ago 3:13

MP3•Epizód kép

The American Association for Thoracic Surgery hosted its 104th Annual Meeting in Toronto at the end of April. There were many outstanding presentations. Edward Soltesz, MD, MPH, Surgical Director of the Kaufman Center for Heart Failure and Recovery and the Program and Director for the Department of Thoracic and Cardiovascular Surgery residency and fellowship training programs, highlights the area of high-risk cardiac surgery with temporary mechanical circulatory support assist. As an expert in the field, he presented Machine Learning-Derived Risk Model to Predict Post-Cardiotomy Cardiogenic Shock in High-Risk Cardiac Surgery Patients.

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