We've updated our Privacy Policy to make it clearer how we use your personal data.

We use cookies to provide you with a better experience, read our Cookie Policy

Machine Learning Could Improve Intensive Care Treatment

News   Jan 25, 2019 | Original Press Release from Princeton School of Engineering and Applied Science

 
Machine Learning Could Improve Intensive Care Treatment

Princeton researchers applied machine learning methods to develop an optimal policy for ordering common blood tests in a hospital’s intensive care unit. From left: Computer science graduate student Niranjani Prasad, electrical engineering graduate student Li-Fang Cheng, and Associate Professor of Computer Science Barbara Engelhardt. Credit: David Kelly Crow

 
 
 

RELATED ARTICLES

Could Poor Brain Connectivity Explain Learning Difficulties?

News

Different learning difficulties do not correspond to specific regions of the brain, as previously thought, say researchers at the University of Cambridge. Instead poor connectivity between 'hubs' within the brain is much more strongly related to children's difficulties.

READ MORE

Could This Robot Help Children With Autism Learn?

News

Researchers have developed personalized learning robots for children with autism, studying whether the robots could autonomously gauge the child’s engagement in long-term, in-home therapeutic interventions.

READ MORE

New Network Links Rat and Artificial Neurons

News

Research on novel nanoelectronics devices has enabled brain neurons and artificial neurons to communicate with each other, opening the door to further significant developments in neural and artificial intelligence research.

READ MORE

 

To personalize the content you see on Technology Networks homepage, Log In or Subscribe for Free

LOGIN SUBSCRIBE FOR FREE