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.
The University of Pennsylvania is teaming with Intel to lead a federation of more than two dozen medical and research centers on an AI system for identifying brain tumors.
Researchers in the U.K. and U.S. have developed an automatic prediction model that can tell if someone is infected with COVID-19 based on symptoms alone.
A convolutional neural network trained and internally validated on more than 15,000 lung CT scans has correctly reclassified indeterminate pulmonary nodules into low-risk or high-risk categories.
An AI algorithm has slightly outperformed neurologists at identifying or ruling out Alzheimer’s disease from MRI brain scans combined with demographic information and neuropsychological test results.
