Blockchain technology has not been fully embraced in healthcare compared to some other industries. However, blockchain’s impact on patient care could be quite massive.   

Some findings from AI in Healthcare’s 2020 Leadership Survey deserve additional attention.

AI’s potential impact on healthcare is largely measured in patient outcomes, cost savings and workflow improvements, but the technology could also be used to rid the world of some of its most shocking behavior: the devastating practice of modern slavery.

Deep learning-based analysis of chest x-rays can be used to predict the pulmonary to systemic flow ratio of patients with congenital heart disease, according to a new study published in JAMA Cardiology.

AI algorithms can improve the quality of brain MRI images, according to new findings published in Neurocomputing.

The United States is still viewed as the world’s leader in researching and developing AI solutions—but could that reputation be at stake?

Researchers have developed a new quantitative framework that evaluates thyroid nodules at a level comparable to two expert radiologists.

Elsevier has launched a new healthcare conference dedicated to how AI and other advanced technologies can help improve cancer care for patients all over the world.

Deep learning-based reconstruction (DLR) can reduce the radiation dose associated with low-dose chest and abdominal CT scans without sacrificing image quality, according to a new study published in the American Journal of Roentgenology.

Unrecognized atrial fibrillation (AFib) is a significant issue, one that grows more and more common as time goes on.