ABSTRACT
Ischemic stroke is prone to recurrence, which is the leading cause of death and disability in stroke. Using predictive model to assess the recurrence risk in patients with ischemic stroke, stratifying risk, and formulating corresponding interventions to reduce the recurrence rate are the core contents of secondary prevention. In this paper, research progress on the prediction of recurrence risks of ischemic stroke recently is summarized from the predicting content or factors, including clinical factors, imaging factors, biological markers and traditional Chinese Medicine syndrome differentiation, and the methods of constructing prediction models about traditional statistical methods and machine learning, in order to provide a reference for clinical work.