PO-04-205 A NOVEL ARTIFICIAL INTELLIGENCE ALGORITHM TO IDENTIFY PATIENTS AT RISK OF SUDDEN CARDIAC ARREST

Sudden cardiac death: role of heart rate variability to identify patients at risk.

a b c b * ̈ Federico Lombardi , Timo H. Makikallio , Robert J. Myerburg , Heikki V. Huikuri Cardiologia, Dipartimento di Medicina, Chirurgia e Odontoiatria, Ospedale S. Paolo, University of Milan, Milan, Italy Division of Cardiology, Department of Medicine, University of Oulu, Kajaanintie 50, 90220 Oulu, Finland Division of Cardiology, Department of Medicine, University of Miami School of Medici...

Cardiac imaging and stress testing asymptomatic athletes to identify those at risk of sudden cardiac death.

Sudden cardiac death in young athletes is rare but tragic. The cardiology community is faced with the challenge of providing a sensible strategy for the prevention of SCD while simultaneously reaffirming that the benefits of regular exercise far outweigh potential risks. At present, there is a broad range of screening recommendations dependent upon country, sporting discipline, and competition ...

Can abnormalities of ventricular repolarisation identify insulin dependent diabetic patients at risk of sudden cardiac death?

OBJECTIVE To study the possible association or QT dispersion and mean QTc intervals, as measured from standard 12 lead electrocardiograms, with baroreceptor-cardiac reflex sensitivity (BRS) in insulin dependent diabetic patients. DESIGN Comparative study of non-invasive assessment of BRS, QT interval, and QT dispersion. SETTING Large teaching hospital. SUBJECTS 31 young asymptomatic, norm...

Sudden Cardiac Arrest

Using Artificial Intelligence to Identify State Secrets

Whether officials can be trusted to protect national security information has become a matter of great public controversy, reigniting a long-standing debate about the scope and nature of official secrecy. The declassification of millions of electronic records has made it possible to analyze these issues with greater rigor and precision. Using machine-learning methods, we examined nearly a milli...