Abstract
Ischemic stroke is one of the typical chronic diseases caused by the degeneration of the neural system, which usually leads to great damages to human beings and reduces life quality significantly. Thereby, it is crucial to extract useful predictors from physiological signals, and further diagnose or predict ischemic stroke when there are no apparent symptoms. Specifically, in this study, we put forward a novel prediction method by exploring sleep related features. First, to characterize the pattern of ischemic stroke accurately, we extract a set of effective features from several aspects, including clinical features, fine-grained sleep structure-related features and electroencephalogram-related features. Second, a two-step prediction model is designed, which combines commonly used classifiers and a data filter model together to optimize the prediction result. We evaluate the framework using a real polysomnogram dataset that contains 20 stroke patients and 159 healthy individuals. Experimental results demonstrate that the proposed model can predict stroke events effectively, and the Precision, Recall, Precision Recall Curve and Area Under the Curve are 63%, 85%, 0.773 and 0.919, respectively.
Highlights
Ischemic stroke is a medical condition, which occurs once the arteries to the brain become blocked, resulting in cell death. [1]
We can obtain the following observations according to Table 2
10-fold cross validation to verify the correctness of the experimental results
Summary
Ischemic stroke is a medical condition, which occurs once the arteries to the brain become blocked, resulting in cell death. [1]. Ischemic stroke is a medical condition, which occurs once the arteries to the brain become blocked, resulting in cell death. Of all strokes [3] It occurs when a blood vessel is blocked by a blood clot which means the blood cannot reach the brain. The cerebral blood flow (CBF) of patients suffering from the ischemic stroke is lower than those of health [4]. Ischemic stroke damages brain cells and leads to the degeneration of the motor function accompanied with depression and anxiety [5]. If ischemic stroke can be predicted in a timely fashion, the quality of life and the health level of the public can be improved significantly
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