Also called personalized medicine, this evolving field makes use of an individual’s genes, lifestyle, environment and other factors to identify unique disease risks and guide treatment decision-making.
Masimo's MightySat Medical is the first FDA-cleared pulse oximeter available to consumers without a prescription, which could disrupt the market for the notoriously inaccurate at-home devices.
MediView’s technologies utilize AR to provide clinicians with 3D “X-ray vision” guidance during minimally invasive procedures and surgeries, while also offering remote collaboration.
An AI-driven approach for detecting an early sign of diabetic retinopathy achieved an accuracy rate of more than 98 percent, according to a study published in Computers in Biology and Medicine. The results could mean a quicker and cheaper solution for diagnosing the disease earlier and possibly prevent loss of eyesight.
Insilico Medicine, a Maryland-based AI company, is partnering with TARA Biosystems to discover and develop new therapies for cardiac disease, the companies announced Jan. 7.
AI applied to an electrocardiogram (EKG) test reliably detected asymptomatic left ventricular dysfunction (ALVD)—a precursor to heart failure—and predicted which patients were most at risk of developing the condition in the future, according to a Mayo Clinic study.
GE Healthcare and the Vanderbilt University Medical Center (VUMC) have partnered to develop diagnostic tools and AI-powered applications to create safer and more precise immunotherapy treatments for cancer patients.
CarePredict, a Florida-based health technology startup, raised $9.5 million in funding for its platform that uses machine-learning-driven wearables to monitor the health and improve the quality of life for senior citizens, according to a report by VentureBeat.
The newest bundled payment program is a money-saver for CMS and Medicare, according to a recent study published in the New England Journal of Medicine. The findings are on par with previous studies that revealed other bundles are achieving their goals of lowering healthcare costs and improving care outcomes.
The protected health information of deidentified individuals may not be private after UC Berkeley researchers used machine-learning techniques to reidentify the health data of some children and adults. The findings could signal a need for legislation that protects and ensures the privacy of personal health data.
