G. Lu

An interpretable machine learning model for predicting prognosis in acute ischemic stroke with large vessel occlusion

Objective To develop and validate an interpretable nomogram that integrates an imaging score, clinical characteristics, and machine-learning models to predict 90-day functional outcomes in patients with acute ischemic stroke (AIS) and large-vessel occlusion (LVO). Methods We analyzed 240 AIS patients with anterior circ...