Machine learning analysis of Raman hyperspectroscopy—a technology used to measure the intensity of scattered laser light—has shown strong potential as a screening tool for Alzheimer’s disease when applied to an easily obtainable lab specimen: saliva.
There’s plenty of research into the diagnostic accuracy of medical smartphone apps created to supply clinical decision support (CDS). However, few studies have looked at how helpful these apps are in clinical practice.
International investment firm Morgan Stanley believes odds are strong that Apple will become a major player in healthcare AI, according to an article published Sept. 16 in AppleInsider.
Emerging technologies like AI and robotics have vast potential to improve healthcare. Few question this. What remains unclear is how meaningful the advances will be to healthcare providers and, more to the point, the patients they serve.
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.
GE Healthcare has received a green light from the FDA to market a product that embeds AI algorithms in mobile X-ray machines. The system sends an alert to a physician if it detects signs of a collapsed lung as soon as a chest X-ray image is acquired.
Looking to keep “compassion fatigued” call-center workers from growing increasingly insensitive to customers over the course of a workday, Humana’s mail-order pharmacy business has deployed AI-based software that sends reminders aimed at keeping the empathy consistent.
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.
