Stroke is characterized by a high recurrence rate, and intervention after early identification of patients at risk of recurrence may improve their prognosis. After strict screening, 55 patients were enrolled in this study. the results show that it is feasible to identify patients with recurrent cerebrovascular events within one year by integrating clinical and imaging features through machine learning. RandomForest and NaiveBayes are the optimal algorithms, and HCR（hypoperfusion cubage ratio）can significantly optimize the recognition of these patients.
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