Machine learning models for outcome prediction in thrombectomy for large anterior vessel occlusion.
Journal:
Annals of clinical and translational neurology
PMID:
39180278
Abstract
OBJECTIVE: Predicting long-term functional outcomes shortly after a stroke is challenging, even for experienced neurologists. Therefore, we aimed to evaluate multiple machine learning models and the importance of clinical/radiological parameters to develop a model that balances minimal input data with reliable predictions of long-term functional independency.