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.
Machine learning (ML) can provide significant value in the field of palliative care. However, researchers still have a lot of unexplored ground to cover before the technology reaches its full potential.
Chun Yuan, PhD, has received a two-year, $200,000 grant from the American Heart Association’s Institute for Precision Cardiovascular Medicine for his work on using AI to detect blocked arteries and cardiovascular risk.
Researchers have developed a multitask deep learning model that can effectively assess signs of hip osteoarthritis in x-rays, sharing their findings in Radiology.
The rise of AI in healthcare—especially radiology—has launched countless conversations about ethics, bias and the difference between “right” and “wrong.”
Radiology researchers are turning to deep learning (DL) technology to make NLP even more effective—and it’s a growing trend that shows no signs of slowing down.
AI can help improve malaria screening in low-resource settings, according to a new study published in the Journal of Digital Imaging. The model developed by researchers is as precise as human experts—and “several orders of magnitude” faster.
Radiology researchers have been spent countless hours seeking a dose-reduction technique that provides high-quality images while still limiting the patient’s exposure to ionizing radiation as much as possible.
