A new study at Centre for Eye Research Australia featuring an AI-powered smart camera is helping identify people who require urgent treatment resulting from a headache serious enough to warrant a visit to hospital.
The AI algorithm powering the smart camera has already been trialled in the lab and will soon be put to the test in real-world settings.
Project leader Dr Lisa Zhuoting Zhu said that with the support of a grant from the Ramaciotti Foundation, her team can determine the feasibility of implementing the camera in a busy emergency department.
Zhu said many Australians may get a headache bad enough to warrant a trip to their local hospital at least once in their life.
After being triaged, referred to have a CT scan and then enduring the nervous wait for results, most patients will generally be diagnosed with a ‘primary headache’.
Primary headaches include migraines and tension headaches and – while serious – are often resolved with pain medication and rest.
However, Zhu said a small percentage of patients are diagnosed with a ‘secondary headache’, such as a brain haemorrhage or a tumour, which often lead to a life-threatening amount of pressure on the brain.
“We want to help emergency department physicians screen these patients as soon as possible, because a delayed diagnosis could potentially be fatal,” she said.
In the study, Zhu’s team at CERA will use the smart camera to help emergency department physicians pinpoint papilledema – a swelling of the optic disc and a tell-tale sign of high pressure in the brain.
Zhu said that every emergency department already has the tool to examine a patient’s optic disc, however, the available technology makes it extremely difficult for physicians to perform the exam and interpret the data – so the check is rarely performed.
The goal of Zhu’s research is that the physician would only need to tell the patient to move into position, and then the camera would automatically take a picture and send it to the AI algorithm for interpretation.
“Thirty to 60 seconds later, the patient could have a diagnosis of papilledema,” Zhu said.
After trialling the smart camera in the emergency department for at least six months, Zhu plans to refine the algorithm and then aim towards potentially bringing the camera into more emergency departments throughout Australia.
Zhu was recently awarded a Victoria Fellowship in Life Sciences to advance her work using AI technology to predict chronological age based on images of the retina, and aims to apply this technology to even more uses.
“In the near future, we can hopefully make an even bigger impact by trialling the smart camera in emergency departments to detect not only life-threatening but also sight-threatening conditions.”
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