AI knows when you’re going to die. But unlike in sci-fi movies, that information could end up saving lives.

A new paper published in Nature suggests that feeding electronic health record data to a deep learning model could substantially improve the accuracy of projected outcomes. In trials using data from two U.S. hospitals, researchers were able to show that these algorithms could predict a patient’s length of stay and time of discharge, but also the time of death.

The neural network described in the study uses an immense amount of data, such as a patient’s vitals and medical history, to make its predictions. A new algorithm lines up previous events of each patient’s records into a timeline, which allowed the deep learning model to pinpoint future outcomes, including time of death.

The neural network even includes handwritten notes, comments, and scribbles on old charts to make its predictions. And all of these calculations in record time, of course.

AI, of course, already has a number of other applications in healthcare. A pair of recently developed algorithms could diagnose lung cancer and heart disease even more accurately than human doctors. Read more from…

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