/PRNewswire/ Ahead of World Stroke Day, October 29, physicians from the Get Ahead of Stroke® campaign are highlighting a sobering statistic: While the.
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Today at the Society of NeuroInterventional Surgery’s (SNIS) 20th Annual Meeting, researchers discussed a smartphone app created that reliably recognizes patients’ physical signs of stroke with the power of machine learning.
In the study, “Smartphone-Enabled Machine Learning Algorithms for Autonomous Stroke Detection,” researchers from the UCLA David Geffen School of Medicine and multiple medical institutions in Bulgaria used data from 240 patients with stroke at four metropolitan stroke centers. Within 72 hours of the start of the patients’ symptoms, researchers used smartphones to record videos of patients and test their arm strength in order to detect patients’ facial asymmetry, arm weakness, and speech changes all classic stroke signs.