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.
Cynthia Rudin, PhD, is a highly regarded computer scientist who’s been eyeing the advance of artificial intelligence into society with equal parts enthusiasm and concern.
By now it’s a difficult-to-dispute likelihood: AI won’t replace doctors making diagnoses, but doctors who use AI will displace doctors who don’t use AI. The hypothesis gets a fresh airing out from the vantage point of the general public.
“With new mutations of the virus with higher transmission rates, it is imperative to diagnose positive cases as quickly and accurately as possible,” researchers wrote.
Researchers have used unsupervised machine learning to predict disease-causing properties in more than 36 million genetic variants across more than 3,200 disease-related genes.
New research shows horizontal gene transfer is predictable in bacteria by machine learning, a development that could lead to better weapons in the war against E. coli and other bacterial assailants that collaborate to conquer pharmacologic first responders.
U.S. health systems are increasingly leveraging digital health to conduct their operations, but how health systems are using digital health in their strategies can vary widely.
When human counselors are unavailable to provide work-based wellness coaching, robots can substitute—as long as the workers are comfortable with emerging technologies and the machines aren’t overly humanlike.
A vendor that supplies EHR software to public health agencies is partnering with a health-tech startup in the cloud-communications space to equip state and local governments for managing their response to the COVID-19 crisis.