Computed tomography (CT) and magnetic resonance imaging (MRI) play an important role in the early identification of ischemic stroke; however, the capability in predicting functional outcome is limited.

Converting medical images into high-throughput quantitative features, radiomics, has been applied in the prediction of clinical outcomes.

The novel noninvasive clinical-radiomics nomogram encompassing patient characteristics and the radiomics signature shows good performance in predicting ischemic stroke prognosis.