Development of rapid and effective risk prediction models for stroke in the Chinese population: a cross-sectional study

Conclusion The five machine learning models all had good predictive and discriminatory performance for stroke. The performance of RF and XGBoost was slightly better than that of LR, which was easier to interpret and less prone to overfitting. This work provides a rapid and accurate tool for stroke risk assessment, which can help to improve the efficiency of stroke screening medical services and the management of high-risk groups.
Source: BMJ Open - Category: General Medicine Authors: Tags: Open access, Public health Source Type: research