AI is set to disrupt every field and every industry. Healthcare, in particular, seems primed for disruption. Here’s an interesting project out of Stanford.

“One of the really exciting things about computer vision is that it’s this powerful measuring tool,” said Yeung, who will be joining the faculty of Stanford’s department of biomedical data science this summer. “It can watch what’s happening in the hospital setting continuously, 24/7, and it never gets tired.”

Current methods for documenting patient movement are burdensome and ripe for human error, so this team is devising a new way that relies on computer vision technology similar to that in self-driving cars. Sensors in a hospital room capture patient motions as silhouette-like moving images, and a trained algorithm identifies the activity — whether a patient is being moved into or out of bed, for example, or into or out of a chair.

TensorFlow Meets Chip Huyen (@chipro), author and instructor of the TensorFlow for Deep Learning class at Stanford University: In this video, she discusses the class, her journey from writing travel stories, to studying computer science, to now teaching students about deep learning at Stanford University!