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.

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.

When patients and family members discuss end-of-life matters with professional caregivers, the silences between words can be as telling as the words themselves.

A health-management company in Arizona is expanding its use of AI to detect risk factors in Medicare Advantage patients by scanning doctors’ notes to automatically flag patients who need additional reimbursable care.