More than 500 clinical AI algorithms have now been cleared by the FDA, with the majority just in the past couple years.

Radiomics features could be especially useful for determining TSS in scenarios where clinical data is lacking or unreliable, such as when patients have altered mental status.

Sanjay Parekh, PhD, senior market analyst with Signify Research, explains how some radiology AI is being adopted outside of radiology departments to improve care.

Bibb Allen, MD, FACR, chief medical officer of the American College of Radiology (ACR) Data Science Institute, explains the trend of using AI for the automated detection of stroke on computed tomography (CT) imaging and the need to include radiologists on the stroke care team.

Experts involved in the research believe their findings could help to guide providers in making treatment decisions. 

Triaging patients with stroke-like symptoms using MRI with diffusion-weighted imaging (DWI) could reduce the cost burden associated with unnecessary neurovascular imaging procedures. 

The protocol does not come at the expense of deteriorated image quality, according to work published recently in the European Journal of Radiology.

Researchers recently revamped the database in the hopes of expanding algorithm development in the field of stroke care.