GE Healthcare has joined an Australian AI-powered project aimed improving the diagnosis and monitoring of brain aneurysms.

One of the medical specialties highly hopeful in AI’s potential to guide care is neurosurgery. That’s because patients with traumatic brain injuries often present care teams and family members with an especially thorny decision. 

Machine learning can accurately predict which patients will not live beyond 30 days after discharge from the ER, giving these patients time to discuss end-of-life care with family members and hospice professionals.

Researchers on the International Space Station are leveraging the microgravity conditions within the ISS U.S. National Laboratory to study heart cells in ways we can’t on the ground.

Patients whose blood glucose levels spike during surgery are at heightened risk for poor overall outcomes. A new AI tool has proven effective at predicting, prior to surgery, which patients will have the problem while under the knife.

Cerner Corporation has partnered with the Duke Clinical Research Institute to pilot the Cerner Learning Health Network, an evolving database that aims to automate data collection for rapid access to contemporary medical information.

Colorado’s UCHealth system has extended the reach of “Livi,” an AI-powered virtual assistant it introduced early this year, from its website to patients’ smart speakers.

A large health data-sharing consortium based in Pittsburgh is bringing in Amazon Web Services to help drive research and product development around machine learning and cloud computing in numerous areas of healthcare.