AI promises to make a titanic impact on radiology, but most of the attention tends to focus on its ability to identify important findings in medical images. What about the technology’s non-interpretive qualities?

In the near future, patients may have their blood drawn and tested by an advanced robot—and it’s a move that would benefit both patients and healthcare providers.

Researchers have found they can use microbe samples—and a little help from machine learning techniques—to predict someone’s age.

XRHealth has announced the launch of a new telehealth clinic that allows patients to receive care at home via virtual reality (VR) technology.

Big-name Chinese technology vendors have responded to the Wuhan coronavirus outbreak by using more AI surveillance on the general public than ever before.

Machine learning-based algorithms can predict how patients will respond to antidepressants, according to new research published in Nature Biotechnology. The secret, the authors revealed, is electroencephalography (EEG) data.

Olaris has received a new grant from The Michael J. Fox Foundation for Parkinson’s Research (MJFF).

Deep learning-based AI models can improve the segmentation of white matter in 18F-FDG PET/CT images, according to a new study published in the Journal of Digital Imaging. This helps radiologists with the early diagnosis of neurodegenerative disease.

President Trump’s 2021 budget proposal included significant cuts related to healthcare and science research, but AI received additional funding compared to 2020.

Blockchain technology is starting to gain popularity in the healthcare industry due to its ability to keep data safe and secure. So what do physicians and patients think about this growing trend?