Integration of the Extreme Gradient Boosting model with electronic health records to enable the early diagnosis of multiple sclerosis

Ruoning Wang,Wenjing Luo,Zifeng Liu, Weilong Liu,Chunxin Liu,Xun Liu,He Zhu,Rui Li,Jiafang Song,Xueqiang Hu,Sheng Han,Wei Qiu

Multiple Sclerosis and Related Disorders（2021）

引用 8|浏览22

暂无评分

摘要

•The performance of five algorithms in early diagnosis of MS was compared.•Extreme Gradient Boosting (XGBoost) had a higher recall, specificity, and precision.•XGBoost showed the best performance in both training and test sets.•61%, 51%, and 49% of patients could be diagnosed with MS, 1, 2, and 3 years earlier.•Our model was effective to help reduce MS diagnostic delays.

查看译文

关键词

Baysian optimization,early diagnostics,machine learning algorithms,MS,XGBoost

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要