Applying Machine Learning to Carotid Sonographic Features for Recurrent Stroke in Patients With Acute Stroke.

Shih-Yi Lin,Kin-Man Law,Yi-Chun Yeh,Kuo-Chen Wu, Jhih-Han Lai,Chih-Hsueh Lin,Wu-Huei Hsu,Cheng-Chieh Lin,Chia-Hung Kao

Frontiers in cardiovascular medicine（2022）

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摘要

When using the CatBoost model, the top three features for predicting recurrent stroke were determined to be the use of anticoagulation medications, the use of NSAID medications, and the resistive index of the left subclavian artery. The CatBoost model demonstrated efficiency and achieved optimal performance in the predictive classification of non-recurrent and recurrent stroke.

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关键词

CatBoost model,acute stroke,carotid sonographic features,machine learning,recurrent stroke

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