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.
NYU Langone Health’s Department of Radiology is planning to release a large-scale dataset that includes more than 1.5 million MRI knee images in an ongoing effort to make MRI scans faster with AI.
After using deep learning on patient scans to track cancer evolution, one research team is hopeful the “promising results” can help improve treatment response and survival predictions for cancer patients.
A physician whose research produced promising results for using AI to improve the detection of tuberculosis (TB) was awarded the Alexander R. Margulis Award for Scientific Excellence during the annual RSNA conference in Chicago.
University of Oxford researchers were able to predict a patient’s risk of being admitted into emergency care by using machine-learning techniques with electronic health records (EHRs), according to a study published in PLOS Medicine.
A deep-learning algorithm was significantly faster and just as accurate as most radiologists in analyzing chest X-rays for several diseases, according to a study led by Stanford University researchers.
With the help of machine learning, researchers were able to train a computer to analyze breast cancer images and classify tumors accurately, according to a study published in NPJ Breast Cancer.
