Patients can now use AI to monitor their glucose levels with off-the-shelf, noninvasive wearable sensors, according to a new study published in Scientific Reports.

MyndYou, a New York City-based healthcare technology company, will now be working with Allscripts clients to monitor their patients for cognitive changes and avoid hospitalization whenever possible.

Radiomics and machine learning can help healthcare providers determine if late gadolinium enhancement (LGE) on cardiac MR images is a sign of myocardial infarction (MI) or myocarditis.

Researchers from the University of California Irvine (UCI) School of Medicine have received $1.2 million to study the potential psychological impact of augmented reality (AR) medical simulation training.

Aidoc announced Monday, Jan. 13, that its AI solution for detecting large-vessel occlusions (LVOs) in head CTA examinations has gained FDA clearance.

Students can use virtual reality (VR) training to learn about radiographic hand positioning skills, according to a new study published in Radiography. How would this compare to other training techniques?

Cardiologs, a cardiology diagnostics company with offices in Paris and Boston, has raised $15 million in Series A funding.

Exploring electronic medical records (EMRs) can help healthcare providers learn more about typical treatment patterns for specific situations, according to new findings published in Artificial Intelligence in Medicine.

Researchers have found a new way to predict AI’s impact on the U.S. workforce: paying close attention to patents.

Deep learning could potentially assist healthcare providers with the evaluation of small renal masses detected on certain contrast-enhanced CT exams, according to a new study published in the American Journal of Roentgenology.

Machine learning (ML) technology has gained popularity in recent years, but its use in healthcare remains largely limited to proof-of-concept academic studies, according to a new study published in Artificial Intelligence in Medicine.

Researchers have developed a deep learning system capable of evaluating tissue samples and diagnosing prostate cancer at a level comparable with many pathologists.