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

İçerik Cleveland Clinic Heart & Vascular Institute, Cleveland Clinic Heart, and Vascular Institute tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Cleveland Clinic Heart & Vascular Institute, Cleveland Clinic Heart, and Vascular Institute veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

7M ago 3:13

MP3•Bölüm sayfası

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.

299 bölüm

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