The machine learning model predicted stroke with 84% accuracy. It was also highly sensitive, outperforming existing diagnostic models, which tend to miss up to 30% of strokes.

However, despite improvements in managing complications associated with the use of CF-LVADs, stroke continues to be a major adverse event after the implantation of the device. Medical Xpress ...

Researchers at Penn State are using machine learning and existing electrocardiogram (ECG) data to help doctors make more accurate predictions. A team of artificial intelligence engineers, in ...