Health
New tool can diagnose stroke on smartphone
According to one study, researchers have developed machine learning models to support and potentially speed up the diagnostic process by physicians in the clinical setting.
New York: A new tool created by researchers can accurately diagnose a stroke within minutes of all-smartphone interaction, based on the patient’s speaking ability and abnormal facial muscle movements.
According to one study, researchers have developed machine learning models to support and potentially speed up the diagnostic process by physicians in the clinical setting.
“Currently, doctors need to use past training and experience to determine when to send a patient to a CT scan,” said James Wang, a research author at Pennsylvania State University in the United States.
“We’re trying to use a machine learning approach to simulate or emulate this process,” Wang added.
The team’s novel approach is to suspect a stroke by identifying abnormalities in the patient’s face and voice, such as sagging cheeks and indistinct speech, using computational facial movement analysis and natural language processing. We analyzed the presence of stroke in a patient in a real emergency room.
To train computer models, researchers created a dataset from more than 80 patients experiencing stroke symptoms at the Houston Methodist Hospital in Texas.
Each patient was asked to perform a speech test to analyze speech and cognitive communication while being recorded on the Apple iPhone.
“Obtaining facial data in the natural environment makes our job robust and useful in real-world clinical use, ultimately enhancing the method of remote diagnosis of stroke and self-assessment,” Huang said. I have.
When testing the model on the Houston Methodist dataset, researchers found that its performance achieved 79% accuracy. This is comparable to a clinical diagnosis by a physician in the emergency room using additional tests such as CT scans.
However, this model can evaluate a patient in just 4 minutes, which helps save valuable time in diagnosing a stroke.
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