Geisinger has tapped IBM’s AI expertise and come up with a way to predict hospital patients’ risk of sepsis. In the process, the method can increase chances of survival in those who have the tricky and potentially life-threatening condition.

A single heartbeat is all a new neural-network technique needs to detect heart failure with 100% accuracy, according to a study slated for January 2020 publication in Biomedical Signal Processing and Control Journal.

Chicago biotech company BIOLIFE4D announced this week it had successfully 3D-bioprinted a mini human heart—something the company noted as a “significant milestone” on the path to printing full-sized hearts viable for transplant.

Proven protocols and practices, people and a push for earlier hemodynamic support are changing the face of cardiogenic shock survival. One leading health system has improved survival rates into the 70+ percent range. And their team believes other facilities should follow suit.

Researchers have developed a system combining AI and mHealth to catch signs of impending suicidal behavior in time for interventions by caregivers.

An AI-based smartphone app for detecting cancer in skin lesions has proven quite capable, achieving 95.1% sensitivity.

Intermountain Healthcare has opened an AI-powered service line for patients with chronic kidney disease and end-stage renal disease.

There’s still a long way to go with both research into Alzheimer’s disease and AI tools to help detect it, but deep-learning approaches continue to show promise for classifying the condition on images of the brain.