Development and Validation of an Interpretable Machine Learning Model for Prediction of the Risk of Clinically Ineffective Reperfusion in Patients Following Thrombectomy for Ischemic Stroke

Development and Validation of an Interpretable Machine Learning Model for Prediction of the Risk of Clinically Ineffective Reperfusion in Patients Following Thrombectomy for Ischemic Stroke

Xiaolong Hu,1,2,* Dayong Qi,2,* Suya Li,2 Shifei Ye,2 Yue Chen,2 Wei Cao,2 Meng Du,2 Tianheng Zheng,2 Peng Li,2 Yibin Fang1– 3 1Tongji University School of Medicine, Tongji University Affiliated Shanghai 4th People’s Hospital, Shanghai, People’s Republic of China; 2Department...

Full description

Saved in:
Bibliographic Details
Main Authors: Hu X, Qi D, Li S, Ye S, Chen Y, Cao W, Du M, Zheng T, Li P, Fang Y
Format: Article
Language:English
Published: Dove Medical Press 2025-05-01
Series:Therapeutics and Clinical Risk Management
Subjects:
machine learning
clinically ineffective reperfusion
predictive model，acute ischemic stroke
online predictive platform.
Online Access:https://www.dovepress.com/development-and-validation-of-an-interpretable-machine-learning-model--peer-reviewed-fulltext-article-TCRM
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items