关键词: 缺血性卒中, 预后预测, 机器学习, 预测模型, 综述

Abstract: Acute ischemic stroke（AIS）is characterized by high rates of disability，mortality，and recurrence，posing a significant burden on patients and society. In the era of big data，predictive models are increasingly used in patient diagnosis，treatment decisions，prognosis management，and healthcare resource allocation，highlighting their growing importance. Machine learning methods have become a crucial tool for predicting the prognosis of AIS patients and have been widely applied. This review explores recent advancements in the study of AIS prognosis prediction，focusing on machine learning methods. It discusses current issues and challenges faced by machine learning models，aiming to provide new insights and references for methods of early assessment and prediction of prognosis outcomes in AIS patients.

Key words: Ischemic stroke, Prognosis prediction, Machine learning, Prediction model, Review