When having a stroke, a swift diagnosis is important. Now, a new AI based tool could diagnose a stroke within minutes simply through a smartphone.
Novel tool can diagnose stroke with the accuracy of an emergency room clinician from interaction with a smartphone, reports a new study. The tool can diagnose a stroke based on abnormalities in a patient's speech ability and facial muscular movements within minutes from an interaction with a smartphone.
‘New machine learning model aids in potentially increases the speed of stroke diagnosis in a clinical setting. ’
According to a study, researchers have developed a machine learning model to aid in and potentially speed up the diagnostic process by physicians in a clinical setting. "Currently, physicians have to use their past training and experience to determine at what stage a patient should be sent for a CT scan," said study author James Wang from Penn State University in the US.
"We are trying to simulate or emulate this process by using our machine learning approach," Wang added.
The team's novel approach analyzed the presence of stroke among actual emergency room patients with suspicion of stroke by using computational facial motion analysis and natural language processing to identify abnormalities in a patient's face or voice, such as a drooping cheek or slurred speech.
To train the computer model, the researchers built a dataset from more than 80 patients experiencing stroke symptoms at Houston Methodist Hospital in Texas.
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"The acquisition of facial data in natural settings makes our work robust and useful for real-world clinical use, and ultimately empowers our method for remote diagnosis of stroke and self-assessment," said Huang.
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However, the model could help save valuable time in diagnosing a stroke, with the ability to assess a patient in as little as four minutes.
Source-IANS