Andrew Rosenberg, MD, chief information officer for Michigan Medicine, mentioned to Health Data Management that the organization currently has 34 ongoing AI and machine leaning projects including the MCIRCC developed automated computer algorithm that utilizes data from a single lead of a non-invasive electrocardiograph signal for analysis and early identification of hemodynamic decline.

Analytic for Hemodynamic Instability—is a novel application of continuous nonlinear pattern recognition through the analysis of heart rate variability, which can detect signs of hemodynamic decompensation prior to overt changes in vital signs over very short periods of time.

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