Innovation

There is still much work to be done before artificial intelligence reaches its full potential in healthcare, but high-tech initiatives have already begun to boost hospital and health system efficiency and improve patient outcomes.

Cleveland Clinic researchers developed an artificial neural network that analyzes lung cancer patients' EHRs and medical scans to determine the most effective radiation dosage for therapy, according to a study published in the Lancet Digital Health.

University of California San Francisco has opened a $275-million cancer center that will use precision medicine to offer patients tailored treatments, including immunotherapy, genetic counseling and clinical trials.

The American College of Radiology has recruited five more health systems to participate in a pilot program that will tailor an artificial intelligence model to the unique imaging needs of each of seven participating systems.

Nashville, Tenn.-based Change Healthcare announced June 24 the integration of artificial intelligence technology into its existing claims management solutions to automatically identify claims that could result in denials.

The University of Missouri broke ground June 21 on the NextGen Precision Health Institute, which will serve all four of its universities, its affiliated health system and many industry partners and will be based on the Columbia, Mo., campus.

Using a machine learning algorithm to analyze blood volume data gathered by commercial smartwatches is a reliable screening system for hypertrophic cardiomyopathy (HCM), according to a study published June 24 in npj Digital Medicine.

Scientists have developed a brain-computer interface allowing an individual to control a robotic arm with only their neural signals, without the need for invasive brain implants.

A system that compiles artificial intelligence-generated imaging data into one place for radiologist analysis has been determined ready for commercialization by the FDA, according to Foster City, Calif.-based TeraRecon, a developer of digital radiology solutions.

Researchers from Verily, Alphabet's life sciences arm, developed a deep learning algorithm that can identify diabetic retinopathy with equal or better accuracy than that of trained human experts, according to a study published this month in JAMA Ophthalmology.