Territory-wide cohort study of Brugada syndrome in Hong Kong: predictors of long-term outcomes using random survival forests and non-negative matrix factorisation.
Sharen LeeJiandong ZhouKa Hou Christien LiKeith Sai Kit LeungIshan LakhaniTong LiuIan Chi Kei WongNgai Shing MokChloe MakKamalan JeevaratnamQingpeng ZhangGary TsePublished in: Open heart (2021)
Clinical history, electrocardiographic markers and investigation results provide important information for risk stratification. Machine learning techniques using NMF and RSF significantly improves overall risk stratification performance.