A new smartphone tool may help ensure that happens, by allowing first responders to determine if a patient has indeed experienced a stroke.

The symptoms of strokes can often be subtle and/or ambiguous.

In such cases, patients have to be assessed via a series of tests once they reach the hospital. If those tests indicate that a stroke has occurred, then the real treatment begins. However, if doctors knew that an incoming patient was already a confirmed stroke victim, then treatment could start as soon as that person reached the hospital.

That's where the experimental smartphone tool comes in.

Developed by a team of scientists from Australia's RMIT University, the software uses AI algorithms to analyze a video of the patient's face as they're told to smile. If the muscle movements of their face are found to be overly asymmetric, then the software alerts its user that the patient has recently experienced a stroke.

The system utilizes the existing Facial Action Coding System, in which facial expressions are broken down into individual components of muscle movement called Action Units.

"One of the key parameters that affects people with stroke is that their facial muscles typically become unilateral, so one side of the face behaves differently from the other side of the face," says the lead scientist, PhD scholar Guilherme Camargo de Oliveira. "We've got the AI tools and the image processing tools that can detect whether there is any change in the asymmetry of the smile – that is the key to detection in our case."