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 ...

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

Stroke risk prediction tools are meant to guide how doctors approach a potentially deadly condition. But a new analysis finds several work less well for Black patients.

To clear things up, I drew you this flowchart on the back of an envelope so you can work out whether something is using AI or not. This originally appeared in our AI newsletter The Algorithm.