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.
AI can detect brain hemorrhages in CT scans more accurately than some radiologists, according to new findings published by Proceedings of the National Academy of Sciences.
Deep learning algorithms can be trained to flag suspicious chest x-rays in an emergency department (ED) setting, according to new research published in Radiology.
Researchers have trained a machine learning model to identify patients with familial hypercholesterolemia (FH), a genetic disorder that increases a person’s risk of coronary artery disease.
Deep learning can be used to predict the future hospitalization of pediatric patients, according to new research published in the American Journal of Managed Care.
Working alongside machine learning technology can help radiologists detect more breast cancers, according to new findings published in IEEE Transactions on Medical Imaging.
Compensation for heart specialists continues to climb. What does this say about cardiology as a whole? Could private equity's rising influence bring about change? We spoke to MedAxiom CEO Jerry Blackwell, MD, MBA, a veteran cardiologist himself, to learn more.
The American College of Cardiology has shared its perspective on new CMS payment policies, highlighting revenue concerns while providing key details for cardiologists and other cardiology professionals.
As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”
